CN103297179B - A kind of method and apparatus generating channel quality instruction - Google Patents

Abstract

The invention discloses a kind of method and apparatus generating channel quality indicator (CQI)。The method includes internal ring processing procedure and/or outer loop process process。Wherein, in internal ring processing procedure, according to the measured value of signal to noise ratio and signal to noise ratio Changing Pattern, it is possible to obtain the predictive value of signal to noise ratio, and then obtain the first CQI value。In outer shroud processing procedure, obtain CQI side-play amount according to the magnitude relationship of Block Error Rate estimated value with Block Error Rate threshold value。According to the first CQI value and CQI side-play amount, the second CQI value can be obtained。Additionally optional modulation system, to generate complete CQI。The method adopting the present invention, it is possible to match CQI better and come into force the channel quality in moment, and can effectively control Block Error Rate, thus being greatly improved the feedback oscillator of CQI so that the throughput of terminal and service delay be improved significantly。

Description

Method and device for generating channel quality indication

Technical Field

The present invention relates to the field of communications technologies, and in particular, to a method and an apparatus for generating a channel quality indicator.

Background

According to the 3GPP protocol, when the system has downlink data to transmit, a NodeB (node B, i.e. a base station) first transmits downlink scheduling and control information on a downlink shared control channel, for example, on a high speed shared control channel (HS-SCCH).

Then, high speed downlink shared channel (HS-DSCH) resources are scheduled to be transmitted to the terminal.

And the terminal receives the HS-DSCH channel resource and measures to obtain a Channel Quality Indicator (CQI) according to the timing relation between the resource granted by the HS-SCCH and the HS-DSCH.

The generation of CQI is generally obtained by searching a SNR code rate table according to the measured SNR or SIR of the HS-DSCH traffic channel to obtain a code rate corresponding to the SNR or SIR, and according to the current resource situation of the HS-DSCH.

According to the 3GPP protocol, the purpose of CQI estimation is to obtain maximum single transmission throughput on the premise that the transport channel block error rate (BLER) is not greater than 10%.

Wherein the single transmission throughput is (1-BLER) x RTBS,

and the RTBS reports the recommended transmission block size of the CQI for the user equipment.

The User Equipment (UE) should send on the next available high speed shared information channel (HS-SICH) of the HS-DSCH transmission corresponding to a CQI report for the HS-DSCH.

Fig. 1 shows a timing diagram. The HS-SCCH2 indicated by the black dashed line in the figure corresponds to HS-DSCH2, while the resulting CQI report on HS-DSCH2 is sent on HS-SICH 1. When the base station uses the CQI report for resource scheduling, the fastest time is to be on HS-SCCH4, and HS-DSCH4 corresponding to HS-SCCH4 is two sub-frames later than HS-DSCH2 on which the CQI report is generated. In other words, the time when the CQI report is obtained on the HS-DSCH2 is the time when the CQI report is generated, and the time when the resource scheduling is performed on the HS-SCCH4 by using the CQI report is the time when the CQI report becomes effective. And a CQI time delay of two sub-frames exists between the moment when the CQI report takes effect and the moment when the CQI report is generated.

In fig. 1, the CQI delay is two subframes. In some special cases, the CQI report is used by the base station at a later time, so the CQI delay may be greater than two subframes.

The present inventors have conducted intensive studies on the above method and found that the above method has at least the following problems:

in the prior art, a code rate is generated according to a channel quality measurement value obtained on the current HS-DSCH, and then CQI is obtained and reported. Since the channel quality on which the CQI report is based is different from the channel quality at the moment when the CQI report becomes effective, it is disadvantageous to satisfy the condition of maximum throughput for a single transmission.

That is, in the prior art, the CQI delay is not considered, the CQI is generated and reported in the nth subframe, and the report is applied to the (n + D) th subframe for resource scheduling. However, the channel quality of the (n + D) th subframe may not be consistent with the channel quality of the nth subframe, which is not favorable for satisfying the condition of maximum throughput of single transmission.

Specifically, the actual channel quality of the n + D subframe may be better or worse than the channel quality of the n subframe. If the signal-to-noise ratio of the (n + D) th subframe is larger than that of the nth subframe, the reported CQI is small, and the throughput rate is influenced by the undersized CQI; if the signal-to-noise ratio of the (n + D) th subframe is smaller than that of the nth subframe, the reported CQI is larger, and the HS-DSCH demodulation block error rate is high due to the excessively large CQI report, so that the rate is low and the system is unstable.

Disclosure of Invention

The inventor of the present invention finds that the above-mentioned prior art has a problem that the channel quality based on the CQI report is different from the channel quality at the time when the CQI report becomes effective, and proposes a new technical solution for the problem, so as to obtain the snr prediction value of the channel at the time when the CQI report becomes effective.

According to an aspect of the invention, a method of generating a channel quality indication is provided. The method comprises the following steps: step A, obtaining the change rule of the signal-to-noise ratio of a channel according to the signal-to-noise ratio of a current subframe (nth subframe) received from the channel and the signal-to-noise ratios of m subframes received from the channel before the current subframe; and step B, acquiring the signal-to-noise ratio predicted value of the (n + D) th subframe of the channel according to the acquired signal-to-noise ratio change rule. And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

Preferably, the change rule of the signal-to-noise ratio of the channel can be that the signal-to-noise ratio randomly fluctuates, or can be that the signal-to-noise ratio continuously increases or continuously decreases.

Step B may comprise: selecting a signal-to-noise ratio prediction mode corresponding to a change rule of a signal-to-noise ratio of a channel according to the change rule; and when the signal-to-noise ratio continuously increases or continuously decreases at the current subframe and m subframes before the current subframe, obtaining a signal-to-noise ratio predicted value by using the first prediction mode. The first prediction mode is to obtain a weighted average value of the signal-to-noise ratio variation of adjacent sub-frames according to the signal-to-noise ratios of a current sub-frame and m sub-frames before the current sub-frame, and obtain the signal-to-noise ratio predicted value of the n + D sub-frame according to the weighted average value, or predict the variation speed of the signal-to-noise ratio from the signal-to-noise ratio of the current sub-frame to the signal-to-noise ratio of the n + D sub-frame, and obtain the signal-to-noise ratio predicted value of the.

When the signal-to-noise ratio fluctuates randomly between the current sub-frame and the previous m sub-frames, a signal-to-noise ratio predicted value can be obtained by using the second prediction mode. The second prediction mode is to take the average value of the signal-to-noise ratios of the current sub-frame and the previous m sub-frames as the signal-to-noise ratio prediction value of the n + D sub-frame of the channel; or, performing smooth filtering on the signal-to-noise ratios of the current subframe and the previous m subframes, and taking the obtained smooth value of the signal-to-noise ratio as a predicted value of the signal-to-noise ratio of the (n + D) th subframe of the channel.

Preferably, the step of selecting the snr prediction mode may comprise:

and counting the prediction success rate, wherein the prediction success rate is the probability that the signal-to-noise ratio is detected to continuously increase or continuously decrease within the statistical window of the prediction success rate.

The prediction success rate is compared with the first power threshold value Th1 and the second power threshold value Th 2. Wherein, the first power threshold is larger than the second power threshold.

And when the prediction success rate is greater than the first success rate threshold value, selecting a first prediction mode for processing. And when the prediction success rate is smaller than the second power threshold value, selecting a second prediction mode for processing.

When the prediction success rate is between the first power-forming threshold value and the second power-forming threshold value, using the signal-to-noise ratio of the current sub-frame as a signal-to-noise ratio prediction value after a plurality of sub-frames of the channel,

wherein Th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25.

Preferably, the first power-saving threshold may be 0.4, and the second power-saving threshold may be 0.2.

Preferably, the step of statistically predicting the success rate may include:

and for each subframe in the prediction success rate statistic window, judging whether the signal-to-noise ratio from the previous mth subframe to the subframe continuously increases or continuously decreases. If so, the subframe is predictable, otherwise the subframe is unpredictable.

The prediction success rate is the ratio of the number of predictable subframes in a prediction success rate statistic window to the total number of subframes in the window. The prediction success rate statistical window may be a sliding window.

Optionally, the step of obtaining the snr prediction value using the first prediction mode may include:

obtaining a signal-to-noise ratio predicted value of a D-th sub-frame after the current sub-frame by using the signal-to-noise ratio change values of the current sub-frame and adjacent sub-frames in m sub-frames before the current sub-frame and by using the following signal-to-noise ratio prediction formula:

$\mathrm{SNR}(\hat{n}+D)=\mathrm{snr}\left(n\right)+[k_1,k_2,...,k_j,...,k_m]\×\left[\begin{array}{c}\mathrm{\Δ}{\mathrm{snr}}_1\\ \mathrm{\Δ}{\mathrm{snr}}_2\\ ...\\ \mathrm{\Δ}{\mathrm{snr}}_j\\ ...\\ \mathrm{\Δ}{\mathrm{snr}}_m\end{array}\right]\×D\×\mathrm{\γ},$ wherein,

Δsnr₁＝snr(n)-snr(n-1)，

Δsnr₂＝snr(n-1)-snr(n-2)，

…

Δsnr_j＝snr(n-j+1)-snr(n-j)，

…

Δsnr_m＝snr(n-m+1)-snr(n-m)，

m is any positive integer, snr (n) is the signal-to-noise ratio of the current sub-frame, snr (n-j) is the signal-to-noise ratio of the j sub-frame before the current sub-frame, k_jIs Δ snr_jK is 0. ltoreq. k_jIs less than or equal to 1, andgamma is a predicted correction factor when delta snr is used_jWhen both are greater than 0, gamma is a positive real number less than 1, and when delta snr is greater than_jWhen both are less than 0, γ is a positive real number greater than 1.

Preferably, when Δ snr is_jWhen both are greater than 0, γ is 0.9. When Δ snr is_jWhen both are less than 0, γ is 1.1.

Preferably, the weighting coefficients are adaptively obtained by:

a plurality of candidate weighting coefficient groups are set. And obtaining a plurality of signal-to-noise ratio predicted values of the current sub-frame, namely the nth sub-frame by utilizing the signal-to-noise ratios from the (n-D-m) th sub-frame to the (n-D) th sub-frame and the plurality of candidate weighting coefficient groups according to a signal-to-noise ratio prediction formula. And selecting the signal-to-noise ratio predicted value closest to the signal-to-noise ratio measured value of the current subframe from the plurality of signal-to-noise ratio predicted values. And taking the candidate weighting coefficient group corresponding to the selected SNR predicted value as the weighting coefficient group of the current sub-frame.

Preferably, when m is 3, the three weighting coefficients are: k is a radical of₁＝0.40，k₂＝0.35，k₃＝0.25。

Optionally, in the first prediction mode, the step of obtaining a predicted value of the signal-to-noise ratio according to the speed of change of the signal-to-noise ratio may include:

using the SNR variation values of the current sub-frame and the adjacent sub-frames in the m sub-frames before the current sub-frame, and obtaining the predicted value of the SNR of the D sub-frame after the current sub-frame according to the following SNR prediction formula,

$\mathrm{SNR}(\hat{n}+D)=\mathrm{snr}\left(n\right)+\mathrm{\Δsnr},$

wherein, Δ snr ═ a Δ²+ B Δ + C, Δ ═ snr (n) -snr (n-1), coefficients A, B and C are obtained from the signal-to-noise ratio of a number of subframes preceding the subframe and by the following equation:

$\left\{\begin{array}{c}\mathrm{snr}\left(n\right)-\mathrm{snr}(n-D)=A{(\mathrm{snr}\left(n\right)-\mathrm{snr}(n-1))}^2+B(\mathrm{SNR}\left(n\right)-\mathrm{snr}(n-1))+C\\ \mathrm{snr}(n-1)-\mathrm{snr}(n-D-1)=A{(\mathrm{snr}(n-1)-\mathrm{snr}(n-2))}^2+B(\mathrm{snr}(n-1)-\mathrm{snr}(n-2))+C\\ \mathrm{snr}(n-2)-\mathrm{snr}(n-D-2)=A{(\mathrm{snr}(n-2)-\mathrm{snr}(n-3))}^2+B(\mathrm{snr}(n-2)-\mathrm{snr}(n-3))+C\end{array}\right.$

preferably, the step of smoothing the signal-to-noise ratio may comprise:

performing linear smoothing filtering processing or logarithmic smoothing filtering processing on the signal-to-noise ratios of the current subframe and the previous m subframes by using a filter, wherein the smoothing value of the signal-to-noise ratio is as follows:

$\widetilde{\mathrm{SNR}}\left(n\right)=\mathrm{snr}\left(n\right)\×\mathrm{\α}+\widetilde{\mathrm{SNR}}(n-1)\×(1-\mathrm{\α}),$

wherein snr (n) is the signal-to-noise ratio measurement value of the current subframe, alpha is a smoothing coefficient, and alpha is more than or equal to 0 and less than or equal to 1.

Preferably, the value range of the smoothing coefficient can be 1/8 ≦ α ≦ 1/2.

Preferably, the method further comprises:

and step C, obtaining a code rate corresponding to the predicted signal-to-noise ratio value according to the corresponding relation between the predicted signal-to-noise ratio value and the code rate.

And D, obtaining a channel quality indication sequence number CQIIndex according to the code rate and the scheduling resource quantity of the channel.

Optionally, step C may calculate a code rate corresponding to the snr prediction value by using an snr code rate formula.

Optionally, in step C, the predicted snr value may be substituted into an snr code rate formula, so as to calculate a code rate corresponding to the predicted snr value.

Preferably, the snr-bitrate formula is obtained by:

the average value of the block error rate which maximizes the throughput rate is obtained by computer simulation. The target value of the block error rate is set as the average value of the block error rate. And obtaining the signal-to-noise ratio required by all transmission blocks which can reach the target value of the block error rate according to the target value of the block error rate. And obtaining the signal-to-noise ratio code rate formula according to the code rate corresponding to the transmission block and the obtained signal-to-noise ratio. The snr code rate formula may be:

E_c＝ax²+bx+c

wherein E is_cFor code rate, x is the signal-to-noise ratio, and coefficients a, b, and c can be obtained by simulation.

Preferably, the method further comprises: and E, obtaining the channel quality indication sequence number offset Deta _ CQI. Step E may include:

E1. and counting the CRC result demodulated by the channel in a block error rate segmentation window to obtain the block error rate.

E2. And comparing the block error rate with a first block error rate convergence threshold and a second block error rate convergence threshold, and adjusting the channel quality indication sequence number offset according to the comparison result. The first convergence threshold is greater than the second convergence threshold, and the initial value of the channel quality indicator sequence number offset is zero.

When the block error rate is higher than the first convergence threshold, the current cqi offset is adjusted downward, and the above steps E1 and E2 are performed again.

When the block error rate is lower than the second convergence threshold, the current cqi offset is adjusted up, and the above steps E1 and E2 are performed again.

And when the block error rate is between the first block error rate convergence threshold and the second block error rate convergence threshold, keeping the channel quality indication sequence number offset unchanged.

Preferably, the first block error rate is receivedConvergence threshold is B_t＊F_d. The second convergence threshold is B_t＊F_u. Wherein, B_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

Preferably, F_u＝0.5，，F_d＝1.5。

Preferably, the target value of the block error rate can be adjusted according to the requirement of the quality of service (QOS) level of the service.

Preferably, the step of adjusting according to the QOS level requirement of the service includes: detecting the QoS level of the service; and searching a service block error rate target value adjustment table according to the detected QoS grade to obtain the block error rate corresponding to the QoS grade, and taking the block error rate as the block error rate target value aiming at the service.

Optionally, in an embodiment, the method further comprises after step C, obtaining a correction code rate according to the following formula by using the channel quality indication sequence number offset,

E_new＝E_c＊ (R < Lambda > Deta _ CQI), wherein,

E_newto correct the code rate, E_cAnd C, obtaining the code rate in the step C, wherein R is the proportion between the large blocks and the small blocks between the adjacent transport blocks in the transport block size sequence number table, and the Deta _ CQI is the channel quality indication sequence number offset.

Preferably, the method further comprises: and after the step of obtaining the correction code rate, judging whether the correction code rate exceeds the code rate bearing upper limit of an additive white Gaussian noise AWGN channel. And when the judgment result is yes, carrying the upper limit output code rate according to the code rate of the AWGN channel. And when the judgment result is negative, the correction code rate is kept unchanged.

Optionally, in another embodiment, the method further comprises: after step D, biasing the CQI sequence numberThe sum of the shift amount and the CQI number obtained in step D is used as the adjusted CQI_new。

Preferably, the adjusted channel quality indication CQI is obtained_newAfter the step (b), the method further comprises: utilizing CQI_newAnd searching a transmission block size table to obtain the size of the transmission block. And obtaining the correction code rate according to the size of the transmission block and the quantity of the scheduling resources. And judging whether the correction code rate exceeds the code rate bearing upper limit of the AWGN channel. And when the judgment result is yes, outputting according to the code rate bearing upper limit of the AWGN channel. And when the judgment result is negative, the correction code rate is kept unchanged.

Preferably, the block error rate segmentation window is a sliding window. The window length is W and the sliding step is M. Wherein W, M are positive integers, and M is less than or equal to W.

Optionally, the adjustment of the cqi offset is performed at the bler segment window boundary.

Optionally, the adjustment of the channel quality indication offset is performed inside the block error rate segmentation window. The step of adjusting the channel quality indication offset within the window may comprise:

and judging whether the redundant cyclic check CRC window accumulated on the current subframe reaches the minimum CRC window or not. And when the judgment result is yes, obtaining the block error rate. The block error rate is the ratio of the number of errors of CRC in a redundancy cyclic check CRC window accumulated on the current subframe to the length of a block error rate sectional counting window.

Preferably, the method further comprises: and selecting a modulation mode according to the code rate, the first modulation threshold and the second modulation threshold. Wherein the first modulation threshold is less than the second modulation threshold.

And when the code rate is smaller than the first modulation threshold, selecting a four-phase shift modulation (QPSK). And when the code rate is between the first modulation threshold and the second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols. And when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.

According to another aspect of the invention, an apparatus for generating a channel quality indication is provided. The device includes:

and the signal-to-noise ratio change rule obtaining unit is used for obtaining the change rule of the signal-to-noise ratio of the channel according to the signal-to-noise ratio of the current subframe (namely the nth subframe) received from the channel and the signal-to-noise ratios of m subframes received from the channel before the current subframe.

And the signal-to-noise ratio predicted value obtaining unit is used for obtaining the signal-to-noise ratio predicted value of the (n + D) th subframe of the channel according to the change rule of the signal-to-noise ratio. And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

Preferably, the change rule of the signal-to-noise ratio of the channel is that the signal-to-noise ratio fluctuates randomly or that the signal-to-noise ratio continuously increases or decreases.

The snr prediction value obtaining unit may include:

and the signal-to-noise ratio prediction mode subunit is used for selecting the signal-to-noise ratio prediction mode corresponding to the change rule according to the change rule of the signal-to-noise ratio of the channel.

And the first prediction subunit obtains the signal-to-noise ratio predicted value by utilizing the first prediction mode when the signal-to-noise ratio continuously increases or continuously decreases at the current subframe and m subframes before the current subframe.

The first prediction mode is to obtain a weighted average value of the SNR variation of the adjacent sub-frames according to the SNR of the current sub-frame and the m sub-frames before the current sub-frame, to use the product of the weighted average value and D as the variance prediction value of the SNR of the (n + D) th sub-frame and the current sub-frame, and to use the sum of the variance prediction value of the SNR and the SNR of the current sub-frame as the SNR prediction value, or

Predicting the change speed of the signal-to-noise ratio from the signal-to-noise ratio of the current subframe to the signal-to-noise ratio of the (n + D) th subframe, and obtaining the signal-to-noise ratio predicted value of the (n + D) th subframe according to the change speed.

And the second prediction subunit obtains the signal-to-noise ratio predicted value by using a second prediction mode when the signal-to-noise ratio fluctuates randomly between the current subframe and the previous subframe m.

The second prediction mode is to use the average value of the signal-to-noise ratios of the current sub-frame and the m sub-frames before as the signal-to-noise ratio predicted value after a plurality of sub-frames of the channel, or to carry out smooth filtering on the signal-to-noise ratios of the current sub-frame and the m sub-frames before, and to use the obtained signal-to-noise ratio smoothed value as the signal-to-noise ratio predicted value of the n + D sub-frame of the channel.

Preferably, the snr prediction mode sub-unit may include:

and the prediction success rate counting module is used for counting the prediction success rate. The prediction success rate may be the probability of detecting a sustained increase or sustained decrease in the signal-to-noise ratio within a prediction success rate statistical window. And for each subframe in the prediction success rate statistic window, the prediction success rate statistic module judges whether the signal-to-noise ratio from the previous mth subframe to the subframe continuously increases or continuously decreases. If so, the subframe is predictable, otherwise the subframe is unpredictable. The prediction success rate may be a ratio of the number of predictable subframes in a prediction success rate statistics window to the total number of subframes in the window. The prediction success rate statistical window may be a sliding window.

And the prediction success rate comparison module is used for comparing the prediction success rate with the first power forming threshold value Th1 and the second power forming threshold value Th 2. Wherein, the first power threshold is larger than the second power threshold. When the prediction success rate is larger than the first success rate threshold value, selecting a first prediction subunit for processing; when the prediction success rate is smaller than the second power threshold value, selecting a second prediction subunit for processing; and when the prediction success rate is between the first power-forming threshold value and the second power-forming threshold value, using the signal-to-noise ratio of the current sub-frame as a signal-to-noise ratio prediction value after a plurality of sub-frames of the channel. The value ranges of the first power threshold and the second power threshold may be: th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25.

Preferably, the apparatus may further comprise:

and the code rate obtaining unit is used for obtaining the code rate corresponding to the predicted signal-to-noise ratio value according to the corresponding relation between the predicted signal-to-noise ratio value and the code rate.

And a channel quality indication sequence number obtaining unit, configured to obtain a channel quality indication sequence number CQIindex according to the code rate and the number of scheduling resources of the channel.

Preferably, the apparatus may further comprise: a CQI offset obtaining unit. The unit may include:

and the block error rate counting module is used for counting the CRC result demodulated by the channel in the block error rate segmentation window to obtain the block error rate.

And the block error rate comparison module is used for comparing the block error rate with a first block error rate convergence threshold and a second block error rate convergence threshold and adjusting the channel quality indication sequence number offset according to the comparison result. Wherein the first convergence threshold is greater than the second convergence threshold.

When the block error rate is higher than the first block error rate convergence threshold, the current offset of the channel quality indication sequence number is adjusted downwards, and the block error rate in the block error rate segmentation window is counted again. And when the block error rate is lower than the second block error rate convergence threshold, the current offset of the channel quality indication sequence number is adjusted upwards, and the block error rate in the block error rate segmentation window is counted again. And when the block error rate is between a first block error rate convergence threshold and a second block error rate convergence threshold, keeping the channel quality indication sequence number offset unchanged.

The first block error rate convergence threshold may be B_t＊F_dThe second block error rate convergence threshold may be B_t＊F_u. Wherein, B_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

Preferably, the apparatus may further include a QOS level requirement detection unit and a block error rate target value obtaining unit. The QOS grade requirement detecting unit is used for detecting the QOS grade requirement; and the block error rate target value obtaining unit is used for searching the service block error rate target value adjusting table according to the detected QoS grade so as to obtain the block error rate corresponding to the QoS grade, and the block error rate is used as the block error rate target value aiming at the service.

Preferably, the apparatus may further include a modulation scheme selection unit. The unit is used for selecting a modulation mode according to the code rate, the first modulation threshold and the second modulation threshold. Wherein the first modulation threshold is less than the second modulation threshold. And when the code rate is smaller than the first modulation threshold, selecting a four-phase shift modulation (QPSK). And when the code rate is between the first modulation threshold and the second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols. And when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.

In the technical scheme of the invention, the change rule of the signal-to-noise ratio of the channel is obtained by utilizing the signal-to-noise ratio of the current subframe, namely the nth subframe and the signal-to-noise ratios of m subframes received from the channel before the current subframe. And aiming at different conditions of the signal-to-noise ratio change rule, a corresponding prediction method is adopted, so that the signal-to-noise ratio prediction value of the (n + D) th subframe of the channel is obtained. And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

Therefore, the time delay of the effective time of the CQI report and the generation time of the CQI report is considered by adopting the technical scheme of the invention. By predicting the channel quality at the moment when the CQI report takes effect, the channel quality at the moment when the CQI report takes effect can be better matched, the CQI feedback gain is improved, and the improvement of the throughput and the reduction of the block error rate can be obtained.

Drawings

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description, serve to explain the principles of the invention.

The invention will be more clearly understood from the following detailed description, taken with reference to the accompanying drawings, in which:

fig. 1 is a schematic diagram of a conventional generation timing relationship of CQI reports.

Fig. 2 is a flow diagram of a method of generating a channel quality indication according to one embodiment of the invention.

Fig. 3 is a graph illustrating the variation of the signal-to-noise ratio with time in CASE1 channel environment.

Fig. 4 is a flow diagram of a method of generating a channel quality indication according to another embodiment of the invention.

Fig. 5 is a flow diagram of a method of generating a channel quality indication according to yet another embodiment of the invention.

Fig. 6 is a flowchart of the step of fig. 5 for obtaining the snr prediction value according to the snr variation rule.

Fig. 7 is a flowchart of the steps in fig. 5 for obtaining the cqi sequence number offset.

Fig. 8 is a flowchart of a processing mode in which the window boundary is not reached in the step of obtaining the channel quality indication sequence number offset.

Fig. 9 is a flow diagram of a method of generating a channel quality indication according to yet another embodiment of the invention.

Fig. 10 is a schematic structural diagram of an apparatus for generating a channel quality indication according to an embodiment of the present invention.

Fig. 11 shows a schematic structural diagram of the snr prediction value obtaining unit 12 in fig. 10.

Fig. 12 shows a schematic structure diagram of the snr prediction mode sub-unit 121 in fig. 11.

Fig. 13 is a schematic structural diagram of an apparatus for generating a channel quality indication according to another embodiment of the present invention.

Fig. 14 shows a schematic configuration diagram of the CQI offset obtaining unit 24 in fig. 13.

Fig. 15 is a schematic structural diagram of an apparatus for generating a channel quality indication according to yet another embodiment of the present invention.

Detailed Description

Various exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. It should be noted that: the relative arrangement of the components and steps, the numerical expressions and numerical values set forth in these embodiments do not limit the scope of the present invention unless specifically stated otherwise.

Meanwhile, it should be understood that the sizes of the respective portions shown in the drawings are not drawn in an actual proportional relationship for the convenience of description.

The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.

Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail but are intended to be part of the specification where appropriate.

In all examples shown and discussed herein, any particular value should be construed as merely illustrative, and not limiting. Thus, other examples of the exemplary embodiments may have different values.

It should be noted that: like reference numbers and letters refer to like items in the following figures, and thus, once an item is defined in one figure, further discussion thereof is not required in subsequent figures.

Fig. 2 shows a flow diagram of a method of generating a channel quality indication according to an embodiment of the invention.

In step S101, a variation law of the signal-to-noise ratio of the channel is obtained.

The signal-to-noise ratio of the channel can be estimated using the symbols on the receiver output constellation. In this embodiment, the signal-to-noise ratio, SNR, of the HS-DSCH channel is estimated.

The signal to noise ratio SNR of the acquired HS-DSCH channel may be stored, e.g. the signal to noise ratios of a number of subframes before the current subframe may be recorded by a history window.

Then, according to the stored current value and historical value of the signal-to-noise ratio, the change rule of the signal-to-noise ratio is obtained.

Specifically, the variation rule of the signal-to-noise ratio of the channel can be obtained according to the signal-to-noise ratio of the current subframe (i.e. the nth subframe) received from the channel and the signal-to-noise ratios of m subframes received from the channel before the current subframe.

In the above description, m may be any positive integer. For example, the signal-to-noise ratio of the current subframe and 3-32 subframes before the current subframe may be selected.

The change rule of the signal-to-noise ratio can be that the signal-to-noise ratio fluctuates randomly or the signal-to-noise ratio continuously increases or decreases in a period of time.

For example, in a slowly varying channel environment, such as a PA3, PB3, CASE1 channel environment, the signal-to-noise ratio continuously increases or continuously decreases over a period of time, that is, there is a rising edge and/or a falling edge in the variation curve of the signal-to-noise ratio with time.

Fig. 3 shows a graph of the change of the signal-to-noise ratio with time in CASE1 channel environment. As shown in fig. 3, the portion of the curve a is a rising edge, i.e., the signal-to-noise ratio continuously increases in a period of time, and the portion of the curve B is a falling edge, i.e., the signal-to-noise ratio continuously decreases in a period of time.

In a fast-changing channel environment, such as in the environments of channels VA30 and VA120, since the channel changes very fast and the SNR fluctuation range of the SNR is large, the SNR before two sub-frames is far different from the SNR of the current frame, and the trend of change on the current sub-frame is also different from the previous two frames, i.e. the temporal correlation between the channels is weak and the SNR fluctuates randomly.

Under the environment of a constant channel, such as an AWGN channel, the probability of occurrence of a rising edge and a falling edge is also small due to random fluctuation of the variance of the SNR estimation algorithm itself.

In step S102, a predicted snr value is obtained according to a variation rule of the snr.

According to the change rule of the signal-to-noise ratio, a corresponding prediction method can be adopted to obtain a signal-to-noise ratio prediction value of a D-th subframe (namely an n + D-th subframe) after the current subframe.

And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

Therefore, the obtained signal-to-noise ratio predicted value of the n + D sub-frame is closer to the signal-to-noise ratio true value of the n + D sub-frame.

The channel quality indication generation timing referred to herein means a timing (nth subframe timing) at which a channel quality indication is generated. The time when the cqi becomes effective is the time (the (n + D) th subframe) when the resource is scheduled by using the generated cqi.

Aiming at the change rule of the signal-to-noise ratio under the slowly-varying channel environment, namely that the signal-to-noise ratio continuously increases or continuously decreases at the current subframe and m subframes before the current subframe, a first prediction mode can be selected to obtain a signal-to-noise ratio prediction value.

Specifically, a weighted average of the snr variation of adjacent subframes may be obtained according to the snrs of the current subframe and m subframes before. And taking the product of the weighted average value and D as a variation prediction value of the signal-to-noise ratio of the n + D th subframe compared with the current subframe. The signal-to-noise ratio predicted value is the sum of the signal-to-noise ratio variation predicted value and the signal-to-noise ratio of the current subframe.

The first prediction mode can also predict the change speed of the signal-to-noise ratio from the signal-to-noise ratio of the current sub-frame (namely, the nth sub-frame) to the signal-to-noise ratio of the (n + D) th sub-frame, and obtain the signal-to-noise ratio predicted value of the (n + D) th sub-frame according to the change speed.

Aiming at the signal-to-noise ratio change rule (namely, the signal-to-noise ratio is randomly fluctuated) of the fast-changing channel environment or the signal-to-noise ratio change rule of the invariable channel environment, the prediction method is not applicable any more, and the signal-to-noise ratio prediction value can be obtained by utilizing the second prediction mode.

Specifically, the average value of the signal-to-noise ratios of the current subframe and the m previous subframes may be used as the signal-to-noise ratio prediction value of the n + D subframe of the channel.

In addition, the snr of the current subframe and m subframes before may also be subjected to smoothing filtering, and the obtained snr smoothed value is used as the snr predicted value of the nth + D subframe of the channel.

It should be noted that the method provided by the present invention is not only applicable to the downlink, but also applicable to the uplink.

For downlink, for example, in TD-SCDMA, WCDMA or LTE systems, the receiving end is User Equipment (UE), and the above steps are completed by the UE.

The uplink may also adopt a similar adaptive modulation mode as the downlink, for example, the receiving end generates the transport block size and modulation mode through the test of the quality of the traffic channel and sends them to the sending end, so that the sending end can issue the transport block size and modulation mode that meet the quality of the channel of the receiving end to the receiving end. Thus, the present invention is also suitable for generating the transmission block size and modulation mode report according with the channel quality by the uplink receiving end (namely, the base station).

In the technical scheme of the invention, the change rule of the signal-to-noise ratio in a period of time is obtained by analyzing the signal-to-noise ratio of the current subframe and the historical subframe, and the signal-to-noise ratio at the effective moment of the CQI report is predicted according to the rule. According to the scheme, the subframe delay of the CQI report generation time and the subframe delay of the CQI report effective time are considered, and the signal-to-noise ratio predicted value of the CQI report effective time obtained by the prediction method is more consistent with the signal-to-noise ratio true value of the CQI report effective time, so that the CQI report reported based on the signal-to-noise ratio predicted value is more accurate, and the maximization of single transmission throughput is facilitated.

Fig. 4 shows a flow diagram of a method of generating a channel quality indication according to another embodiment of the invention.

In step S201, a variation law of the signal-to-noise ratio of the channel is obtained.

In this step, the variation rule of the signal-to-noise ratio of the channel can be obtained according to the signal-to-noise ratio of the nth subframe received from the channel and the signal-to-noise ratios of the m subframes previously received from the channel.

In step S202, a predicted snr value is obtained according to a variation rule of the snr.

A corresponding prediction method may be adopted according to the change rule of the signal-to-noise ratio obtained in step S201 to obtain a signal-to-noise ratio prediction value of the D-th subframe, i.e., the n + D-th subframe, after the current subframe.

Where D may be any positive integer, for example, the snr prediction value of any subframe after the current subframe may be obtained. Preferably, D is the number of delayed subframes between the time of generating the channel quality indicator and the time of taking effect of the channel quality indicator, so that the obtained snr prediction value is exactly the snr prediction value at the time of taking effect of the channel quality indicator.

Step S201 and step S202 in this embodiment may be the same as step S101 and step S102 in the previous embodiment, respectively, and are not described again here.

In step S203, a code rate corresponding to the predicted snr value is obtained by using the correspondence between the predicted snr value and the code rate.

In this step, the code rate corresponding to the predicted snr value can be obtained by looking up the snr code rate table.

However, the method of obtaining the code rate by looking up the table requires a large amount of data tables to be stored, thereby occupying a certain storage space. Furthermore, this method also requires reading the memory area multiple times and comparing the size, thereby increasing the complexity of implementation.

Preferably, another method can be adopted to obtain the code rate corresponding to the predicted snr value.

The method is to fit a signal-to-noise ratio code rate formula through computer simulation. Then, the obtained signal-to-noise ratio is substituted into the signal-to-noise ratio code rate formula to calculate the code rate.

The signal-to-noise ratio code rate formula can be obtained by the following method:

first, an average block error rate value that maximizes the throughput is obtained by computer simulation. A preferred AWGN channel maximizes the throughput with a mean block error rate of 1%.

Then, the block error rate target value is set as the block error rate average value.

And then, according to the target value of the block error rate, acquiring the signal-to-noise ratio required by all the transmission blocks which can reach the target value of the block error rate.

According to the code rate corresponding to the transmission block and the obtained signal-to-noise ratio, a signal-to-noise ratio code rate formula can be obtained. The snr code rate formula may be:

E_c＝ax²+bx+c

wherein E is_cThe code rate, x the signal-to-noise ratio, and the coefficients a, b, and c are obtained by simulation.

By adopting the method, the code rate corresponding to the input signal-to-noise ratio can be obtained by one-step operation, and the realization complexity is low.

It should be noted that the snr-code rate formula is not limited to the form of the unitary quadratic equation, and any other method or other channel may be used to perform simulation, so as to obtain the relationship between the code rate and the snr.

In step S204, a channel quality indication sequence number CQIindex is obtained according to the code rate and the number of scheduling resources of the channel.

Specifically, the size of the transport block may be calculated by using the code rate obtained in the previous step and the number of the scheduled HS-SCCH resources. Then, the table of the size of the transmission block is searched by using the size of the transmission block, thereby obtaining the corresponding CQI serial number.

Fig. 5 shows a flow diagram of a method of generating a channel quality indication according to yet another embodiment of the invention.

In step S301, a variation law of the signal-to-noise ratio of the channel is obtained.

The change rule of the signal-to-noise ratio of the channel can be obtained according to the signal-to-noise ratio of the current subframe (namely, the nth subframe) and the signal-to-noise ratios of the previous m subframes.

The change rule of the signal-to-noise ratio can be that the signal-to-noise ratio fluctuates randomly or the signal-to-noise ratio continuously increases or decreases continuously.

In step S302, a predicted snr value is obtained according to a variation rule of the snr.

A corresponding prediction method may be adopted according to the change rule of the snr obtained in step S301 to calculate the snr prediction value of the D-th subframe after the current subframe, i.e., the n + D subframe.

Preferably, D is the number of delayed subframes between the time of generating the channel quality indicator and the time of taking the channel quality indicator into effect.

Fig. 6 shows a detailed flowchart of step S302.

In step S3021, a prediction success rate is counted according to signal-to-noise ratios of the current subframe and the historical subframe.

The prediction success rate is the probability of detecting a continuous increase or continuous decrease of the signal-to-noise ratio within a statistical window of the prediction success rate.

Specifically, for each subframe in the prediction success rate statistics window, it may be determined whether the signal-to-noise ratio from the previous mth subframe to the subframe continuously increases or continuously decreases. Wherein m may be any natural number, for example, it may be determined whether the snr of 3 to 32 subframes before the current subframe continuously increases or continuously decreases.

If yes, the subframe is predictable, and can be set to be 1 at the position of the subframe; otherwise, the subframe is unpredictable and may be set to 0 at the subframe location.

Then, the ratio of the number of 1 in the prediction success rate statistical window to the window length W is used as the statistical prediction success rate on the current subframe.

The prediction success rate statistics window may be a sliding window. The sliding step size may be M, where M is any positive integer, that is, the updated prediction success rate may be output every M subframes.

It should be understood by those skilled in the art that the method for recording the success rate statistics result of the present invention is not limited to the scheme of setting 1 or 0 at the subframe position, and other methods may also be used to record the success rate statistics result.

In step S3022, the obtained prediction success rate is compared with the first power control threshold value Th1 and the second power control threshold value Th 2. Wherein, the first power threshold is larger than the second power threshold.

When the prediction success rate is greater than Th1, step S3023 is performed. When the prediction success rate is less than Th2, step S3024 is performed. When the prediction success rate is between Th1 and Th2, step S3026 is performed.

In step S3023, processing is performed using the first prediction mode. Specifically, it is determined whether a rising edge or a falling edge is detected in the current subframe.

When the rising edge or the falling edge is not detected, step S3026 is performed, and the signal-to-noise ratio value of the current subframe is used as the signal-to-noise ratio prediction value. When a rising edge or a falling edge is detected, step S3025 is performed, using the snr prediction value.

The specific process of step S3025 is as follows:

the SNR prediction value of the Dth sub-frame after the current sub-frame can be obtained by the following SNR prediction formula:

$\mathrm{SNR}(\hat{n}+D)=\mathrm{snr}\left(n\right)+[k_1{,k}_2,...,k_j{,...,k}_m]\&times;\left[\begin{array}{c}\mathrm{\&Delta;}{\mathrm{snr}}_1\\ \mathrm{\&Delta;}{\mathrm{snr}}_2\\ ...\\ \mathrm{\&Delta;}{\mathrm{snr}}_j\\ ...\\ \mathrm{\&Delta;}{\mathrm{snr}}_m\end{array}\right]\&times;D\&times;\mathrm{\&gamma;}$

wherein,

Δsnr₁＝snr(n)-snr(n-1)，

Δsnr₂＝snr(n-1)-snr(n-2)，

…

Δsnr_j＝snr(n-j+1)-snr(n-j)，

…

Δsnr_m＝snr(n-m+1)-snr(n-m)，

the signal-to-noise ratio input value may be stored in a buffer register buffer. According to the time sequence, can be respectively recorded as: snr (n), snr (n-1), snr (n-2), snr (n-3).

m is any positive integer, snr (n) is the signal-to-noise ratio of the current sub-frame, snr (n-j) is the signal-to-noise ratio of the j sub-frame before the current sub-frame, k_jIs Δ snr_jK is 0. ltoreq. k_jIs less than or equal to 1, andgamma is a predicted correction factor when delta snr is used_jWhen both are greater than 0, gamma is a positive real number less than 1, and when delta snr is greater than_jWhen both are less than 0, γ is a positive real number greater than 1.

Preferably, when Δ snr is_jWhen both are greater than 0, γ is 0.9. When Δ snr is_jWhen the number of the carbon atoms is less than 0,γ＝1.1。

the weighting coefficient may be a fixed value or may be obtained by an adaptive method.

Preferably, the optimal weighting coefficients can be adaptively matched according to the snr prediction error. The following description will be given taking an example in which each weighting coefficient group includes three weighting coefficients.

Firstly, the possible value combinations of the weighting coefficients can be discretized to obtain the combination with the preferred number. The following table is an example of a preferred weighting factor combination:

group number	K1, K2, K3 values
		1	[1/3，1/3，1/3]
2	[0.4，0.35，0.25]
		3	[0.5，0.3，0.2]
4	[0.6，0.25，0.15]
		5	[0.7，0.2，0.1]
6	[0.8，0.15，0.05]
		7	[0.9，0.075，0.025]
8	[1.0，0，0]

In the above table, the three weighting factors of group 1 are the same, indicating that the weights of the corresponding three snr increments are the same. The set of weighting coefficients is suitable for the case where the signal-to-noise ratio increases linearly. And for the weighting coefficient of the 8 th group, the signal-to-noise ratio increment weight of the current subframe is the largest, so that the method is suitable for the situation of nonlinear increase of the signal-to-noise ratio. This requires a high estimation accuracy of the signal-to-noise ratio input estimate.

Then, the predicted snr values corresponding to the weighting factor groups are obtained respectively. Specifically, a plurality of SNR predictors for a current sub-frame (i.e., nth sub-frame) may be obtained using SNR of the (n-D-m) th sub-frame to the (n-D) th sub-frame and the plurality of candidate weighting coefficient sets according to an SNR prediction formula.

And then selecting the signal-to-noise ratio predicted value closest to the true signal-to-noise ratio value of the current sub-frame from the obtained signal-to-noise ratio predicted values of the current sub-frame, and taking the candidate weighting coefficient group corresponding to the selected signal-to-noise ratio predicted value as the preferred weighting coefficient group of the current sub-frame.

It should be noted that each weighting coefficient group is not limited to three weighting coefficients. It is possible to store more historical values of the signal-to-noise ratio in the storage area and obtain a predicted value of the signal-to-noise ratio with weighting of the variation amount of the more signal-to-noise ratios.

Further, the weighting coefficient may be a fixed value. In a preferred mode, when m is 3, the three weighting coefficients may be: k is a radical of₁＝0.40，k₂＝0.35，k₃＝0.25。

In another embodiment, the method for obtaining the snr prediction value using the first prediction mode may further include: and predicting the change speed of the change quantity of the signal-to-noise ratio from the moment of generating the CQI to the moment of taking the CQI into effect so as to obtain the signal-to-noise ratio predicted value at the moment of taking the CQI into effect.

The method specifically comprises the following steps:

according to the SNR change value of the current sub-frame and the adjacent sub-frame in the m sub-frames before the current sub-frame, the predicted value of the SNR of the D sub-frame after the current sub-frame is obtained by the following SNR prediction formula,

$\mathrm{SNR}(\hat{n}+D)=\mathrm{snr}\left(n\right)+\mathrm{\&Delta;snr},$

wherein, Δ snr ═ a Δ²+ B Δ + C, Δ ═ snr (n) -snr (n-1), coefficients A, B and C may be obtained from the signal-to-noise ratio of a number of subframes preceding the subframe and by the following equation:

$\left\{\begin{array}{c}\mathrm{snr}\left(n\right)-\mathrm{snr}(n-D)=A{(\mathrm{snr}\left(n\right)-\mathrm{snr}(n-1))}^2+B(\mathrm{snr}\left(n\right)-\mathrm{snr}(n-1))+C\\ \mathrm{snr}(n-1)-\mathrm{snr}(n-D-1)=A{(\mathrm{snr}(n-1)-\mathrm{snr}(n-2))}^2+B(\mathrm{snr}(n-1)-\mathrm{snr}(n-2))+C\\ \mathrm{snr}(n-2)-\mathrm{snr}(n-D-2)=A{(\mathrm{snr}(n-2)-\mathrm{snr}(n-3))}^2+B(\mathrm{snr}(n-2)-\mathrm{snr}(n-3))+C\end{array}\right..$

in step S3024, the second prediction mode is selected for processing.

In the second prediction mode, an average value of the signal-to-noise ratios of the current subframe and the previous m subframes may be used as the signal-to-noise ratio prediction value of the n + D subframe of the channel.

Or, performing smooth filtering on the signal-to-noise ratios of the current subframe and the previous m subframes, and taking the obtained smooth value of the signal-to-noise ratio as a predicted value of the signal-to-noise ratio of the (n + D) th subframe of the channel.

For example, an alpha filter may be used for smoothing, and the smoothed snr smoothing value is used as the snr prediction value of the (n + D) th subframe of the channel.

The smoothing process includes two kinds: linear domain smoothing and logarithmic domain smoothing. If the implementation strategy is inclined to report a more aggressive CQI value on a channel without a channel rising and falling edge, and the block error rate BLER is less concerned, the linear domain smoothing processing is preferred; if a more conservative CQI value is reported on a channel without a channel rising and falling edge in an implementation strategy, and the block error rate BLER is more concerned, then logarithmic domain smoothing is preferred.

The smoothed value of the signal-to-noise ratio may be:

$\widetilde{\mathrm{SNR}}\left(n\right)=\mathrm{snr}\left(n\right)\&times;\mathrm{\&alpha;}+\widetilde{\mathrm{SNR}}(n-1)\&times;(1-\mathrm{\&alpha;}),$

wherein snr (n) is the signal-to-noise ratio measurement value of the current subframe, alpha is a smoothing coefficient, and alpha is more than or equal to 0 and less than or equal to 1.

Preferably, the value range of the smoothing coefficient may be: 1/8 is less than or equal to alpha is less than or equal to 1/2.

After that, step S3027 is performed, using the snr average value or the snr smoothed value as the snr prediction value.

When the prediction success rate is between the first power consumption threshold value and the second power consumption threshold value, step S3026 is performed.

In step S3026, the snr of the current subframe is used as an snr prediction value after D subframes of the channel.

Wherein, the range of the first power threshold and the second power threshold may be: th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25.

Preferably, the first power threshold Th1 may be 0.4, and the second power threshold Th2 may be 0.2. And the initial value of the prediction success rate may be set to 0.35.

In step S303, a code rate corresponding to the predicted snr value is obtained by using the correspondence between the predicted snr value and the code rate.

In this step, the code rate corresponding to the predicted snr value can be obtained by searching the snr code rate by using the predicted snr value.

Or, fitting a signal-to-noise ratio code rate formula through computer simulation, and substituting the signal-to-noise ratio into the signal-to-noise ratio code rate formula to calculate the code rate corresponding to the signal-to-noise ratio predicted value.

It should be understood by those skilled in the art that the method for obtaining the code rate is not limited to the above two methods, and any other method can be used as long as the corresponding code rate can be obtained according to the snr prediction value.

Step S303 may be the same as step S203 in the previous embodiment, and is not described herein again.

In step S304, a channel quality indication sequence number offset Deta _ CQI is obtained through a block error rate alignment procedure.

Because the actual channel capacity has a certain difference with the carrying capacity of the used code table, the difference may be better or worse than the channel used for acquiring the code table by simulation, and the difference is represented by a CQI adjustment offset variable Deta _ CQI, and the unit is the number. The adjustment step size of the Deta _ CQI is denoted as cqidewnstep and CQIupstep, which respectively represent the down-regulation step size and the up-regulation step size, and the unit is 1, which represents a CQI number (CQIIndex).

Since the channel characteristics are dynamically changed, such as the mobile speed increases and the multipath profile changes, the Deta _ CQI is a dynamic variable that needs to be maintained.

The channel quality indication sequence number offset Deta _ CQI can be obtained by the following method:

and counting the Cyclic Redundancy Check (CRC) of channel demodulation in the block error rate segmentation window to obtain the block error rate. Preferably, the length of the block error rate segmentation window may be 32 to 128 subframes.

Preferably, CRC samples entering within the block error rate segmentation window may be filtered. For example, for the HS-DSCH channel, a difference between a code rate corresponding to a transport block size actually transmitted on the HS-DSCH channel by the network side and a code rate corresponding to a transport block requested by CQI feedback needs to be considered. When this difference is too large, the demodulation result for the HS-DSCH channel does not reflect the current channel condition, and therefore there is no need to include such CRC samples in the bler segmentation window.

Under normal conditions, the adjustment is generally performed according to a fixed block error rate segmented window length, that is, when a block error rate segmented window boundary is reached, the adjustment is performed once according to the relationship between the block error rate BLER in the window and the block error rate target value BLERtarget.

However, when the number of CRC errors in the window exceeds a certain number, for example, when the number of CRC errors in the window exceeds Blertarget FcDown window length L, the Deta _ CQI can be adjusted downward without waiting for the window boundary to be reached. After the Deta _ CQI is adjusted downward, the window is cleared immediately and buffering of subsequent CRC values begins anew.

Fig. 7 shows a detailed flowchart of step S304.

In step S3041, it is determined whether the current window length reaches the window boundary.

When the determination result is yes, step S3042 is executed; if the determination result is negative, step S3046 is executed, i.e. entering the non-window boundary adjusting mode.

Wherein, the block error rate is obtained by the following method:

and judging whether the redundant cyclic check CRC window accumulated on the current subframe reaches the minimum CRC window or not. And when the judgment result is yes, the ratio of the error number of the CRC in the redundancy cyclic check CRC window accumulated on the current subframe to the length of the block error rate segmented statistical window is the block error rate.

In step S3042, the block error rate is compared with a first block error rate convergence threshold and a second block error rate convergence threshold, and the channel quality indicator sequence number offset is adjusted according to the comparison result. Wherein the first convergence threshold is greater than the second convergence threshold.

When the estimated block error rate is higher than the first block error rate convergence threshold, step S3043 is executed.

In step S3043, the current CQI sequence number offset is adjusted downward, for example, by one fine adjustment offset step, i.e., Deta _ CQI — cqidowntep. And then, storing the current window record into the historical CRC window record, clearing the current CRC window record, and re-executing the steps.

When the block error rate is lower than the second block error rate convergence threshold, step S3045 is executed.

In step S3045, the current CQI offset is adjusted up, for example, by one fine adjustment offset step, that is, the step is Deta _ CQI + CQIupstep. And then, storing the current window record into the historical CRC window record, clearing the current CRC window record, and re-executing the steps.

When the block error rate is between the first block error rate convergence threshold and the second block error rate convergence threshold, step S3044 is executed to keep the Deta _ CQI unchanged. And then, storing the current window record into the historical CRC window record, and clearing the current CRC window record.

In this embodiment, the first block error rate convergence threshold may be B_t＊F_dThe second block error rate convergence threshold may be B_t＊F_uWherein B is_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

Preferably, the coefficient of rise F_u0.5, coefficient of decline F_d＝1.5。

Fig. 8 is a flow chart showing a processing mode in which a window boundary is not reached in the block error rate alignment process.

In step S3046, it is determined whether the current window is not smaller than the minimum window.

Preferably, the minimum window length may be 6-16.

If the determination result is yes, step S3047 is executed, and if the determination result is no, no operation is executed, and the waiting is continued.

In step S3047, the block error rate is compared with a first block error rate convergence threshold and a second block error rate convergence threshold, and the channel quality indicator sequence number offset is adjusted according to the comparison result. Wherein the first convergence threshold is greater than the second convergence threshold.

When the block error rate is higher than the first block error rate convergence threshold, step S3048 is executed.

In step S3048, the current channel quality indication sequence number offset, that is, Deta _ CQI — cqidewnstep, is adjusted downward. And then, storing the current window record into the historical CRC window record, clearing the current CRC window record, and re-executing the steps.

When the block error rate is lower than the second block error rate convergence threshold, step S30410 is executed.

In step S30410, the current channel quality indicator sequence number offset, that is, Deta _ CQI is Deta _ CQI + CQIupstep. And then, storing the current window record into the historical CRC window record, clearing the current CRC window record, and re-executing the steps.

When the block error rate is between the first block error rate convergence threshold and the second block error rate convergence threshold, step S3049 is executed to keep the channel quality indication sequence number offset unchanged. And then, storing the current window record into the historical CRC window record, and clearing the current CRC window record.

Wherein the first block error rate convergence threshold is B_t＊F_dThe second convergence threshold of the block error rate is B_t＊F_u，B_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

Preferably, the coefficient of rise F_u＝0.5，Coefficient of decline F_d＝1.5。

Preferably, if the number of CRC errors is 0 from the end of the previous window to the current window position, the Deta _ CQI is immediately up-regulated so that the Deta _ CQI is Deta _ CQI + CQIupstep. The historical CRC window record and the current CRC window record are then emptied.

By adopting the Deta _ CQI adjusting process, the CQI can be quickly adjusted up when the channel is good, and the CQI can be quickly adjusted down when the channel is poor.

Preferably, the target value of the block error rate can be adjusted according to the requirement of the service Quality (QOS) level of the service. Thus, different target values of the block error rate can be set according to different service types, and the target values of the block error rate are used for the block error rate statistics in the outer loop control, and the QoS can be selected by a user independently.

For example, for a service (e.g., a mobile banking service) with a small traffic but high information delivery reliability, in order to ensure service reliability, a user may set the Qos level to be the highest through a user interface before performing a banking operation. Then, the terminal obtains the Qos level of the service through detection, and performs a service block error rate target value adjustment table query operation by using the Qos level. The block error rate obtained by table lookup can be used as the target value of the block error rate in the CQI generation process. The target value obtained by the method is relatively low, and the low target value of the block error rate ensures that CQI feedback is more conservative, thereby increasing the transmission reliability of a wireless channel.

When a user is performing a service such as FTP multithreading downloading, the Qos level can be adjusted to a low level requirement in pursuit of the maximum downloading rate. Correspondingly, the target value of the block error rate obtained by detecting the Qos level of the service and performing table lookup is relatively large. In this case, this approach sacrifices channel reliability in exchange for a higher download rate. Moreover, due to the multi-thread downloading, the downloading failure rate is controllable.

When the user performs a single-thread download service (such as music walkman download), the reliability of the channel is required to be higher than that of multi-thread download. Accordingly, a lower target value of the block error rate can be obtained by setting a higher Qos level, thereby avoiding a high probability of download failure.

For the user, the user is willing to sacrifice the success rate for the download rate or sacrifice a small amount of download rate for the success rate, and can set the Qos and obtain the corresponding target value of the block error rate according to the set Qos. The method can map and adjust the grade of the BLER target value according to the intention of the user, provides diversified and personalized selection for the user, and ensures that the user experience is higher.

It should be noted that obtaining the corresponding block error rate according to the QoS of the service is not limited to the table lookup method, and other methods may be used to select the appropriate block error rate.

In step S304, the block error rate BLER is counted, and the code rate can be adjusted according to the counted BLER, so as to control the BLER to the target value. By adopting the method, the block error rate BLER can be accurately controlled to the target value of the block error rate or the block error rate can be controlled within a specific range.

In step S305, a correction code rate is obtained.

In this step, a modified code rate may be obtained using the Deta _ CQI according to the following formula,

E_new＝E_c＊ (R < Lambda > Deta _ CQI), wherein,

E_newto correct the code rate, E_cAnd C, obtaining the code rate in the step C, wherein R is the proportion between the large blocks and the small blocks between the adjacent transmission blocks in the transmission block size sequence number table.

In step S306, the output code rate is constrained to the upper limit of the channel code rate.

In this step, it needs to be determined whether the obtained correction code rate exceeds the code rate bearing upper limit of the channel.

For example, it can be determined whether the modified code rate exceeds the code rate carrying upper limit of the additive white gaussian noise AWGN channel. When the judgment result is yes, carrying an upper limit output code rate according to the code rate of the AWGN channel; and when the judgment result is negative, the correction code rate is kept unchanged.

It should be noted that if the adopted code table is a code table simulated under the AWGN channel, this step may be omitted.

In step S307, a channel quality indication sequence number CQIindex is obtained.

In this step, the transport block size TBsize may be calculated according to the code rate obtained in the previous step and the number of scheduling resources of the channel. Then, the transport block size is used to search the transport block size table, thereby obtaining the CQI sequence number.

In step S308, a modulation scheme is obtained according to the code rate.

In this step, a modulation scheme may be selected according to the code rate, the first modulation threshold, and the second modulation threshold. Wherein the first modulation threshold is less than the second modulation threshold.

When the code rate is smaller than a first modulation threshold, selecting a four-phase shift modulation mode QPSK;

when the code rate is between a first modulation threshold and a second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols;

and when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols. The value range of the first modulation threshold value can be 0.35-0.45, and the value range of the second modulation threshold value can be 0.6-0.63.

It should be noted that the value ranges of the first modulation threshold and the second modulation threshold may be obtained by a computer simulation method, which is related to the receiver scheme adopted by the terminal. Therefore, the ranges of the values of the first modulation threshold and the second modulation threshold are not limited to the above values.

In step S309, CQI reporting may be completed according to the CQIindex obtained above and the selected modulation scheme.

Fig. 9 shows a flow diagram of a method of generating a channel quality indication according to yet another embodiment of the invention.

Step S401 to step S404 belong to an inner loop processing flow of CQI, that is, a predicted value of the signal-to-noise ratio is obtained according to the measured value of the signal-to-noise ratio, and then CQIindex is obtained.

In step S401, a variation law of the signal-to-noise ratio of the channel is obtained.

The change rule of the signal-to-noise ratio of the channel can be obtained according to the signal-to-noise ratio of the current subframe, namely the nth subframe, received from the channel and the signal-to-noise ratio of the m previous subframes.

In step S402, a predicted snr value is obtained according to a variation rule of the snr.

According to the change rule of the signal-to-noise ratio, a corresponding prediction method is adopted to obtain a signal-to-noise ratio prediction value of the D sub-frame after the current sub-frame, namely the n + D sub-frame.

And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

In step S403, a code rate corresponding to the predicted snr value is obtained by using the correspondence between the predicted snr value and the code rate.

In this step, the code rate corresponding to the predicted snr value can be obtained by searching the snr code rate by using the predicted snr value.

Or, fitting a signal-to-noise ratio code rate formula through computer simulation, and substituting the signal-to-noise ratio into the signal-to-noise ratio code rate formula to calculate the code rate corresponding to the signal-to-noise ratio predicted value.

In step S404, a first CQIindex is calculated according to the code rate and the number of scheduling resources.

Step S401, step S402, step S403, and step S404 in this embodiment may be the same as step S301, step S302, step S303, and step S307 in the previous embodiment, and are not described again here.

Step S405 to step S407 belong to an outer loop processing procedure, that is, a CQI offset is obtained through a block error rate alignment procedure.

In step S405, the block error rate is counted.

The block error rate is the ratio of the number of errors of CRC in a redundancy cyclic check CRC window accumulated on the current subframe to the length of a block error rate sectional counting window.

In step S406, the counted block error rate is compared with a first block error rate convergence threshold and a second block error rate convergence threshold. Wherein the first convergence threshold is greater than the second convergence threshold.

In step S407, an offset amount Deta _ CQI of the CQI is obtained according to the comparison result.

Specifically, when the estimated block error rate is higher than the first block error rate convergence threshold, one fine tuning offset step may be decreased; when the block error rate is lower than a second block error rate convergence threshold, a fine tuning offset step length can be increased; when the block error rate is between the first and second block error rate convergence thresholds, the Deta _ CQI may be kept unchanged.

The above steps S405 to S407 belong to the outer loop processing. The block error rate can be effectively controlled through the alignment process of the block error rate. The outer loop processing procedure may be the same as step S304 in the previous embodiment, and will not be described in detail here.

In step S408, a second CQIindex value may be obtained using the first CQIindex value and the CQI offset value obtained through the inner loop processing and the outer loop processing, respectively.

In step S409, a modulation mode is selected according to the code rate, the first modulation threshold, and the second modulation threshold. Wherein the first modulation threshold is less than the second modulation threshold.

When the code rate is smaller than a first modulation threshold, selecting a four-phase shift modulation mode QPSK;

when the code rate is between a first modulation threshold and a second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols;

and when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.

In step S410, a CQI report is generated. This includes the obtained second CQIindex value and the selected modulation scheme.

In the technical solution provided in this embodiment, the inner loop processing can obtain an SNR prediction value according to the SNR measurement value, and obtain the first CQIindex according to the SNR prediction value, which effectively solves the delay problem between the time of generating the CQI report and the time of failure. In the outer loop processing, the block error rate can be effectively controlled through the block error rate comparison process. According to actual measurement, the method provided by the invention can improve the throughput by 50%, and control the block error rate within 10% from 30% or any target value of the block error rate.

Preferably, after obtaining the second CQIindex through step S408, the following operations may also be performed:

firstly, the adjusted channel quality indication sequence number CQIIndex is utilized_newAnd searching a transmission block size table to obtain the size TBsize of the transmission block.

And then, obtaining a correction code rate according to the size of the transmission block and the quantity of the scheduling resources.

And then, constraining the output code rate to the upper limit of the channel code rate.

The step may specifically include determining whether the modified code rate exceeds a code rate loading upper limit of the AWGN channel. When the judgment result is yes, carrying upper limit output according to the code rate of the AWGN channel; and when the judgment result is negative, the correction code rate is kept unchanged.

This step may be omitted if the code table used is a code table simulated under the AWGN channel.

Finally, a third channel quality indication sequence number CQIindex is obtained.

In this step, the transport block size TBsize may be calculated according to the finally output code rate and the number of scheduling resources of the channel. Then, the transport block size is used to search the transport block size table, so as to obtain a third CQI sequence number.

In this embodiment, the block error rate segmentation window is a sliding window, the window length is W, and the sliding step size is M, where W, M are positive integers, and M is less than or equal to W. For example, the sliding step may be 1, or may be the length of the window. When the sliding step length is equal to the window length, the two sliding windows are just connected end to end.

According to another aspect of the present invention, fig. 10 is a schematic structural diagram illustrating an apparatus for generating a channel quality indication according to an embodiment of the present invention.

In this embodiment, the means for generating the channel quality indication comprises a snr variation law obtaining unit 11 and an snr prediction value obtaining unit 12.

The snr variation rule obtaining unit 11 may obtain a variation rule of the snr of the channel according to the snr of a current subframe (i.e., nth subframe) received from the channel and snrs of m subframes received from the channel before the current subframe. m may be any positive integer. For example, the signal-to-noise ratio of the current subframe and 3-32 subframes before the current subframe may be selected.

The signal-to-noise ratio of the channel can be obtained by outputting symbols on a constellation diagram by a receiver and storing the symbols. For example, the signal-to-noise ratio of a number of subframes prior to the current subframe may be recorded by a history window.

The obtained change rule of the signal-to-noise ratio can be that the signal-to-noise ratio randomly fluctuates, or the signal-to-noise ratio continuously increases or continuously decreases in a period of time.

The snr prediction value obtaining unit 12 may obtain the snr prediction value of the (n + D) th subframe of the channel according to the snr change rule obtained by the snr change rule obtaining unit 11, where D is the number of delay subframes between the time of generating the channel quality indicator and the time of taking the channel quality indicator into effect.

The channel quality indication generation timing referred to herein means a timing (nth subframe timing) at which a channel quality indication is generated. The time when the cqi becomes effective is the time (the (n + D) th subframe) when the resource is scheduled by using the generated cqi.

Fig. 11 shows a schematic configuration diagram of the snr prediction value obtaining unit 12.

The snr prediction value obtaining unit 12 includes an snr prediction mode sub-unit 121, a first prediction sub-unit 122, and a second prediction sub-unit 123.

The snr prediction mode sub-unit 121 may select an snr prediction mode corresponding to a change rule of the snr of the channel according to the change rule.

Fig. 12 shows a schematic structure diagram of the snr prediction mode subunit 121.

As shown in fig. 12, the snr prediction mode sub-unit 121 may include a prediction success rate statistics module 1211 and a prediction success rate comparison module 1212.

The prediction success rate statistic module 1211 is configured to count the prediction success rate. The prediction success rate is the probability that the signal-to-noise ratio is detected to continuously increase or continuously decrease within the statistical window of the prediction success rate.

For each subframe in the prediction success rate statistics window, the prediction success rate statistics module 1211 may determine whether the signal-to-noise ratio from the previous mth subframe to the subframe continuously increases or continuously decreases. Wherein m may be any natural number, for example, it may be determined whether the snr of 3 to 32 subframes before the current subframe continuously increases or continuously decreases.

If yes, the subframe is predictable, and can be set to be 1 at the position of the subframe; otherwise, the subframe is unpredictable and may be set to 0 at the subframe location.

Then, the ratio of the number of 1 in the prediction success rate statistical window to the window length W is used as the statistical prediction success rate on the current subframe.

The prediction success rate statistics window may be a sliding window. The sliding step size may be M, where M is any positive integer, that is, the updated prediction success rate may be output every M subframes.

The prediction success rate comparing module 1212 is configured to compare the prediction success rate with the first power threshold Th1 and the second power threshold Th 2. In this embodiment, the first power threshold is greater than the second power threshold.

When the prediction success rate is greater than the first success rate threshold value, selecting the first prediction subunit 122 for processing; when the prediction success rate is smaller than the second power threshold value, selecting the second prediction subunit 123 for processing; and when the prediction success rate is between the first power forming threshold value and the second power forming threshold value, using the signal-to-noise ratio of the current sub-frame as the signal-to-noise ratio prediction value of the (n + D) th sub-frame of the channel. Wherein Th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25. Preferably, the first power threshold Th1 may be 0.4, and the second power threshold Th2 may be 0.2. And the initial value of the prediction success rate may be set to 0.35.

And aiming at different rules of the signal-to-noise ratio, different prediction subunits are selected for processing. Specifically, when the signal-to-noise ratio continuously increases or continuously decreases at the current subframe and m subframes before, the first prediction subunit 122 obtains the signal-to-noise ratio prediction value using the first prediction mode. When the snr fluctuates randomly between the current subframe and the previous subframe m, the second prediction subunit 123 obtains an snr prediction value using the second prediction mode.

The processing of the first prediction sub-unit 122 in the first prediction mode may include: and obtaining a weighted average value of the signal-to-noise ratio variation of the adjacent sub-frames according to the signal-to-noise ratios of the current sub-frame and the m sub-frames before. Then, the product of the weighted average and D is used as a variation prediction value of the signal-to-noise ratio of the n + D th subframe compared with the current subframe. And the signal-to-noise ratio predicted value is the sum of the variation predicted value of the signal-to-noise ratio and the signal-to-noise ratio of the current subframe.

The process can also predict the change speed of the signal-to-noise ratio from the signal-to-noise ratio of the current sub-frame (namely the nth sub-frame) to the signal-to-noise ratio of the (n + D) th sub-frame, and obtain the signal-to-noise ratio predicted value of the (n + D) th sub-frame according to the change speed.

The process of the second prediction sub-unit 123 using the second prediction mode may include: taking the average value of the signal-to-noise ratios of the current sub-frame and the previous m sub-frames as the signal-to-noise ratio predicted value of the n + D sub-frame of the channel; or,

and performing smooth filtering on the signal-to-noise ratios of the current sub-frame and the m sub-frames before the current sub-frame, and taking the obtained smooth value of the signal-to-noise ratio as a predicted value of the signal-to-noise ratio of the (n + D) th sub-frame of the channel.

Fig. 13 is a schematic structural diagram of an apparatus for generating a channel quality indication according to another embodiment of the present invention.

The device comprises a signal-to-noise ratio change rule obtaining unit 21, a signal-to-noise ratio predicted value obtaining unit 22, a code rate obtaining unit 23, a CQI offset obtaining unit 24, a block error rate target value adjusting unit 25, a channel code rate restraining unit 26, a channel quality indication sequence number obtaining unit 27 and a modulation mode selecting unit 28.

The snr change rule obtaining unit 21 is configured to obtain a change rule of the snr of the channel according to the snr of a current subframe, that is, an nth subframe, received from the channel and snrs of m subframes received from the channel before the current subframe.

The snr prediction value obtaining unit 22 is configured to obtain an snr prediction value of the (n + D) th subframe of the channel according to a variation rule of the snr. And D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication.

The snr change rule obtaining unit 21 and the snr predicted value obtaining unit 22 may be respectively the same as the snr change rule obtaining unit 11 and the snr predicted value obtaining unit 12 in the previous embodiment, and are not described herein again.

The code rate obtaining unit 23 may obtain a code rate corresponding to the predicted snr value according to a correspondence between the predicted snr value and the code rate.

Alternatively, the code rate corresponding to the predicted snr value may be obtained by looking up the snr code rate table.

Or fitting a signal-to-noise ratio code rate formula through computer simulation, and substituting the obtained signal-to-noise ratio into the signal-to-noise ratio code rate formula to calculate the code rate.

The signal-to-noise ratio code rate formula can be obtained by the following method:

first, an average block error rate value that maximizes the throughput is obtained by computer simulation. A preferred AWGN channel maximizes the throughput with a mean block error rate of 1%.

Then, the block error rate target value is set as the block error rate average value.

And then, according to the target value of the block error rate, acquiring the signal-to-noise ratio required by all the transmission blocks which can reach the target value of the block error rate.

According to the code rate corresponding to the transmission block and the obtained signal-to-noise ratio, a signal-to-noise ratio code rate formula can be obtained. The snr code rate formula may be:

E_c＝ax²+bx+c

wherein E is_cThe code rate, x the signal-to-noise ratio, and the coefficients a, b, and c are obtained by simulation.

The CQI offset obtaining unit 24 obtains a channel quality indication sequence number offset Deta _ CQI through a block error rate alignment process.

Fig. 14 is a schematic diagram of the structure of the CQI offset acquisition unit 24.

As shown in fig. 14, the CQI offset obtaining unit 24 may include a block error rate statistics module 241 and a block error rate comparison module 242.

The block error rate counting module 241 is configured to count CRC results of channel demodulation within a block error rate segmentation window to obtain a block error rate.

The block error rate comparing module 242 is configured to compare the block error rate with a first block error rate convergence threshold and a second block error rate convergence threshold, and adjust the channel quality indication sequence number offset according to the comparison result. Wherein the first convergence threshold is greater than the second convergence threshold.

When the block error rate is higher than the first block error rate convergence threshold, the current offset of the channel quality indication sequence number is adjusted downwards, and the block error rate in the block error rate segmentation window is counted again.

And when the block error rate is lower than a second block error rate convergence threshold value, the current offset of the channel quality indication sequence number is adjusted upwards, and the block error rate in the block error rate segmentation window is counted again.

And when the block error rate is between a first block error rate convergence threshold and the second block error rate convergence threshold, keeping the channel quality indication sequence number offset unchanged.

The first block error rate convergence threshold is B_t＊F_dThe second block error rate convergence threshold is B_t＊F_uWherein B is_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

In this embodiment, with the Deta _ CQI obtained by the CQI offset obtaining unit 24, the code rate obtained by the code rate obtaining unit 23 can be adjusted according to the following formula:

E_new＝E_c＊ (R < Lambda > Deta _ CQI), wherein,

E_newto correct the code rate, E_cAnd C, obtaining the code rate in the step C, wherein R is the proportion between large blocks and small blocks between adjacent transport blocks in a transport block size sequence number table, and Deta _ CQI is the offset of the channel quality indication sequence number.

The QOS level requirement detecting unit 25 may include a QOS level requirement detecting module 251 and a block error rate target value obtaining module 252. Wherein, the QOS level requirement detecting module 251 is used for detecting the QOS level requirement of the service; the block error rate target value obtaining module 252 is configured to search the service block error rate target value adjustment table according to the detected QoS class to obtain a block error rate corresponding to the QoS class, and use the block error rate as the block error rate target value for the service.

The channel code rate constraining unit 26 may constrain the output code rate to the upper limit of the channel code rate.

Specifically, it may be determined whether the modified code rate exceeds a code rate carrying upper limit of the AWGN channel, and when the determination result is yes, outputting according to the code rate carrying upper limit of the AWGN channel; and when the judgment result is negative, the correction code rate is kept unchanged.

The channel quality indication sequence number obtaining unit 27 may calculate the size TBsize of the transport block according to the finally output code rate and the number of scheduling resources of the channel. Then, the transport block size is used to search the transport block size table, thereby obtaining the CQI sequence number.

The modulation scheme selection unit 28 may select the modulation scheme according to the code rate, the first modulation threshold, and the second modulation threshold. Wherein the first modulation threshold is less than the second modulation threshold.

When the code rate is smaller than a first modulation threshold, selecting a four-phase shift modulation mode QPSK; when the code rate is between a first modulation threshold and a second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols; and when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.

Fig. 15 shows a schematic structural diagram of an apparatus for generating a channel quality indication according to yet another embodiment of the present invention.

As shown in fig. 15, the apparatus includes an snr change rule obtaining unit 31, an snr prediction value obtaining unit 32, a first code rate obtaining unit 33, a CQI offset obtaining unit 34, a block error rate target value adjusting unit 35, a first channel quality indication sequence number obtaining unit 36, a second channel quality indication sequence number obtaining unit 37, a second code rate obtaining unit 38, a channel code rate constraining unit 39, a second channel quality indication sequence number obtaining unit 40, and a modulation scheme selecting unit 41.

The signal-to-noise ratio change rule obtaining unit 31, the signal-to-noise ratio predicted value obtaining unit 32, the first code rate obtaining unit 33 and the first channel quality indication sequence number obtaining unit 36 perform inner loop control to obtain a first CQIindex value; the CQI offset obtaining unit 34 performs outer loop control to obtain a CQI offset.

Compared with the previous embodiment, the difference is that the first CQI obtained by the first channel quality indication sequence number obtaining unit 36 can be adjusted by the Deta _ CQI obtained by the CQI offset obtaining unit 34, so as to directly obtain the second CQIindex value.

Specifically, the sum of the channel quality indication sequence number offset Deta _ CQI and the CQI obtained by the first channel quality indication sequence number obtaining unit 36 is used as the adjusted channel quality indication sequence number CQIindex_newI.e. CQIendex_new＝CQIindex+Deta_CQI。

Then, the adjusted channel quality indication sequence number CQIindex is used by the second code rate obtaining unit 38_newAnd searching a transmission block size table to obtain the size TBsize of the transmission block, and obtaining the correction code rate according to the size of the transmission block and the quantity of scheduling resources. Channel code rate constraint unit 39 for the output code rateAnd (6) carrying out constraint.

Specifically, whether the correction code rate exceeds the code rate bearing upper limit of the AWGN channel is judged, and when the judgment result is yes, the correction code rate is output according to the code rate bearing upper limit of the AWGN channel; and when the judgment result is negative, the correction code rate is kept unchanged.

The third channel quality indication sequence number obtaining unit 40 calculates the size TBsize of the transport block according to the finally output code rate and the number of scheduling resources of the channel. Then, the transport block size is used to search the transport block size table, thereby obtaining the CQI sequence number.

The modulation mode selection unit 41 selects a modulation mode according to the code rate, the first modulation threshold, and the second modulation threshold.

It should be understood by those skilled in the art that the method for recording the success rate statistics result of the present invention is not limited to the scheme of setting 1 or 0 at the subframe position, and other methods may also be used to record the success rate statistics result.

So far, the method and apparatus for generating a channel quality indication according to the present invention have been described in detail. Some details well known in the art have not been described in order to avoid obscuring the concepts of the present invention. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.

Although some specific embodiments of the present invention have been described in detail by way of illustration, it should be understood by those skilled in the art that the above illustration is only for the purpose of illustration and is not intended to limit the scope of the invention. It will be appreciated by those skilled in the art that modifications may be made to the above embodiments without departing from the scope and spirit of the invention. The scope of the invention is defined by the appended claims.

Claims (31)

1. A method of generating a channel quality indication, the method comprising:

step A, obtaining a change rule of the signal-to-noise ratio of the channel according to the signal-to-noise ratio of a current subframe (an nth subframe) received from the channel and the signal-to-noise ratios of m subframes received from the channel before the current subframe, wherein n and m are natural numbers;

b, acquiring a signal-to-noise ratio predicted value of the (n + D) th subframe of the channel according to the change rule of the signal-to-noise ratio, wherein D is the number of delayed subframes between the generation time of the channel quality indication and the effective time of the channel quality indication;

step C, obtaining a code rate corresponding to the predicted signal-to-noise ratio value according to the corresponding relation between the predicted signal-to-noise ratio value and the code rate;

step D, obtaining a channel quality indication sequence number CQIIndex according to the code rate and the scheduling resource quantity of the channel;

wherein the step B comprises:

counting a prediction success rate, wherein the prediction success rate is the probability that the signal-to-noise ratio is detected to continuously increase or continuously decrease in a prediction success rate counting window;

comparing the prediction success rate with a first power threshold Th1 and a second power threshold Th2, wherein the first power threshold is larger than the second power threshold,

when the prediction success rate is larger than the first success rate threshold value, a signal-to-noise ratio prediction value is obtained by utilizing a first prediction mode;

when the prediction success rate is smaller than the second power threshold value, a second prediction mode is selected and utilized to obtain a signal-to-noise ratio prediction value;

when the prediction success rate is between the first power-forming threshold value and the second power-forming threshold value, using the signal-to-noise ratio of the current sub-frame as a signal-to-noise ratio prediction value of the n + D sub-frame of the channel,

wherein Th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25;

wherein the first prediction mode is:

obtaining a weighted average of the SNR variations of adjacent subframes according to the SNR of the current subframe and m subframes before, and obtaining the SNR predicted value of the (n + D) th subframe according to the weighted average, or

Predicting the change speed of the signal-to-noise ratio from the signal-to-noise ratio of the current subframe to the signal-to-noise ratio of the (n + D) th subframe, and obtaining a signal-to-noise ratio predicted value of the (n + D) th subframe according to the change speed;

wherein the second prediction mode is:

taking the average value of the signal-to-noise ratios of the current sub-frame and the previous m sub-frames as the signal-to-noise ratio predicted value of the n + D sub-frame of the channel, or

And performing smooth filtering on the signal-to-noise ratios of the current subframe and the previous m subframes, and taking the obtained smooth value of the signal-to-noise ratio as a predicted value of the signal-to-noise ratio of the (n + D) th subframe of the channel.

2. The method of claim 1,

the change rule of the signal-to-noise ratio of the channel is that the signal-to-noise ratio fluctuates randomly or the signal-to-noise ratio continuously increases or decreases continuously,

the step B comprises the following steps:

selecting a signal-to-noise ratio prediction mode corresponding to a change rule of the signal-to-noise ratio of the channel according to the change rule;

when the signal-to-noise ratio continuously increases or continuously decreases at the current subframe and m subframes before the current subframe, obtaining a signal-to-noise ratio predicted value by using the first prediction mode;

and when the signal-to-noise ratio fluctuates randomly between the current subframe and the previous subframe m, obtaining a signal-to-noise ratio predicted value by using the second prediction mode.

3. The method of claim 1, wherein the first power threshold value is 0.4 and the second power threshold value is 0.2.

4. The method of claim 1, wherein the step of statistically predicting a success rate comprises:

for each subframe in the prediction success rate statistic window, judging whether the signal-to-noise ratio from the previous mth subframe to the subframe continuously increases or continuously decreases, if so, predicting the subframe, otherwise, not predicting the subframe;

the prediction success rate is the ratio of the number of predictable subframes in the prediction success rate statistical window to the total number of subframes in the window, and the prediction success rate statistical window is a sliding window.

5. The method of claim 1, wherein the step of obtaining the snr prediction value using the first prediction mode comprises:

obtaining a signal-to-noise ratio predicted value of a D-th subframe behind the current subframe by using the signal-to-noise ratio change values of the current subframe and adjacent subframes in m subframes before the current subframe and through the following signal-to-noise ratio prediction formula:

$SNR(\hat{n}+D)=snr\left(n\right)+\&lsqb;k_1,k_2,...,k_j,...,k_m\&rsqb;\&times;\left[\begin{array}{c}\mathrm{\&Delta;}sn{r}_1\\ {\mathrm{\&Delta;snr}}_2\\ ...\\ \mathrm{\&Delta;}sn{r}_j\\ ...\\ \mathrm{\&Delta;}sn{r}_m\end{array}\right]\&times;D\&times;\mathrm{\&gamma;},$ wherein,

Δsnr₁＝snr(n)-snr(n-1),

Δsnr₂＝snr(n-1)-snr(n-2),

...

Δsnr_j＝snr(n-j+1)-snr(n-j),

...

Δsnr_m＝snr(n-m+1)-snr(n-m),

m is any positive integer, snr (n) is the signal-to-noise ratio of the current sub-frame, snr (n-j) is the signal-to-noise ratio of the j sub-frame before the current sub-frame, k_jIs Δ snr_jK is 0. ltoreq. k_jIs less than or equal to 1, andgamma is a predicted correction factor when delta snr is used_jWhen both are greater than 0, gamma is a positive real number less than 1, and when delta snr is greater than_jWhen both are less than 0, γ is a positive real number greater than 1.

6. The method of claim 5,

when Δ snr is_jWhen both are more than 0, gamma is 0.9;

when Δ snr is_jWhen both are less than 0, γ is 1.1.

7. The method of claim 5, wherein the weighting coefficients are adaptively obtained by:

setting a plurality of candidate weighting coefficient groups;

according to the signal-to-noise ratio prediction formula, obtaining a plurality of signal-to-noise ratio prediction values of the current sub-frame, namely the nth sub-frame, by utilizing the signal-to-noise ratios from the nth-D-m sub-frame to the nth-D sub-frame and the plurality of candidate weighting coefficient groups;

selecting a signal-to-noise ratio predicted value closest to the signal-to-noise ratio measured value of the current subframe from the plurality of signal-to-noise ratio predicted values;

and taking the candidate weighting coefficient group corresponding to the selected SNR predicted value as the weighting coefficient group of the current sub-frame.

8. The method of claim 7,

when m is 3, the three weighting coefficients are: k is a radical of₁＝0.4，k₂＝0.35，k₃＝0.25。

9. The method of claim 1, wherein in the first prediction mode, the step of obtaining a predicted value of the signal-to-noise ratio according to a speed of change of the signal-to-noise ratio comprises:

using the SNR variation values of the current sub-frame and the adjacent sub-frames in the previous m sub-frames, and obtaining the predicted value of the SNR of the D sub-frame after the current sub-frame according to the following SNR prediction formula,

$SNR(\hat{n}+D)=snr\left(n\right)+\mathrm{\&Delta;}snr,$

wherein, Δ snr ═ a Δ²+ B Δ + C, Δ ═ snr (n) -snr (n-1), coefficients A, B and C are obtained using the signal-to-noise ratio of a number of subframes preceding the subframe and according to the following equation:

$\left\{\begin{array}{c}snr\left(n\right)-snr(n-D)=A{\left(snr\right(n)-snr(n-1\left)\right)}^2+B\left(snr\right(n)-snr(n-1\left)\right)+C\\ snr(n-1)-snr(n-D-1)=A{\left(snr\right(n-1)-snr(n-2\left)\right)}^2+B\left(snr\right(n-1)-snr(n-2\left)\right)+C\\ snr(n-2)-snr(n-D-2)=A{\left(snr\right(n-2)-snr(n-3\left)\right)}^2+B\left(snr\right(n-2)-snr(n-3\left)\right)+C\end{array}\right..$

10. the method of claim 1, wherein in the second prediction mode, the step of smoothing the signal-to-noise ratio comprises:

performing linear average processing or logarithmic average processing on the signal-to-noise ratio of the current subframe and m previous subframes to obtain a smoothed value of the signal-to-noise ratio, wherein the smoothed value of the signal-to-noise ratio is as follows:

$\widetilde{SNR}\left(n\right)=snr\left(n\right)\&times;\mathrm{\&alpha;}+\widetilde{SNR}(n-1)\&times;(1-\mathrm{\&alpha;}),$

wherein snr (n) is the signal-to-noise ratio measurement value of the current subframe, alpha is a smoothing coefficient, and alpha is more than or equal to 0 and less than or equal to 1.

11. The method of claim 10,

1/8≤α≤1/2。

12. the method of claim 1, wherein step C comprises:

obtaining a code rate corresponding to the signal-to-noise ratio predicted value by searching a signal-to-noise ratio code rate table by using the signal-to-noise ratio predicted value; or

And calculating the code rate corresponding to the predicted value of the signal-to-noise ratio by using a signal-to-noise ratio code rate formula.

13. The method of claim 12, wherein the snr-bitrate formula is obtained by:

obtaining the average value of the block error rate which enables the throughput rate to be maximum through computer simulation, and setting the target value of the block error rate as the average value of the block error rate;

obtaining signal-to-noise ratios required by all transmission blocks reaching the target value of the block error rate according to the target value of the block error rate;

obtaining the SNR code rate formula according to the code rate corresponding to the transmission block and the obtained SNR, wherein the SNR code rate formula is as follows:

E_c＝ax²+bx+c

wherein E is_cThe code rate, x the signal-to-noise ratio, and the coefficients a, b, and c are obtained by simulation.

14. The method of claim 1, wherein the method further comprises:

step E, a step of obtaining the channel quality indication sequence number offset Deta _ CQI,

the method comprises the following steps:

E1. counting the cyclic redundancy check result CRC of the channel demodulation in a block error rate segmentation window to obtain a block error rate;

E2. comparing the block error rate with a first block error rate convergence threshold and a second block error rate convergence threshold, and adjusting the channel quality indication sequence number offset according to the comparison result, wherein the first block error rate convergence threshold is greater than the second block error rate convergence threshold, the initial value of the channel quality indication sequence number offset is zero,

when the block error rate is higher than the first convergence threshold, adjusting down the current cqi sequence offset, and re-performing steps E1 and E2;

when the block error rate is lower than the second convergence threshold, adjusting the current cqi sequence offset and re-performing steps E1 and E2;

and when the block error rate is between the first block error rate convergence threshold and the second block error rate convergence threshold, keeping the channel quality indication sequence number offset unchanged.

15. The method of claim 14, wherein the first convergence threshold for block error rate is B_t*F_dThe second block error rate convergence threshold is B_t*F_uWherein B is_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

16. The process of claim 15, F_u＝0.5，F_d＝1.5。

17. The method of claim 14 wherein the block error rate target value is adjusted based on quality of service QOS level requirements of the service.

18. The method of claim 17, wherein the step of adjusting based on quality of service QOS level requirements of the service comprises:

detecting the QoS level of the service;

and searching a service block error rate target value adjustment table according to the detected QoS grade to obtain the block error rate corresponding to the QoS grade, and taking the block error rate as the block error rate target value aiming at the service.

19. The method of claim 14, wherein the method further comprises obtaining a modified code rate using the cqi sequence number offset after step C according to the following formula,

E_new＝E_c(R < Lambda > Deta _ CQI), wherein,

E_newto correct the code rate, E_cAnd C, obtaining the code rate in the step C, wherein R is the proportion between large blocks and small blocks between adjacent transport blocks in a transport block size sequence number table, and Deta _ CQI is the offset of the channel quality indication sequence number.

20. The method of claim 19, wherein the method further comprises, after the step of obtaining a revised code rate,

judging whether the correction code rate exceeds the code rate bearing upper limit of an additive white Gaussian noise AWGN channel or not,

when the judgment result is yes, carrying an upper limit output code rate according to the code rate of the AWGN channel;

and when the judgment result is negative, the correction code rate is kept unchanged.

21. The method of claim 14, wherein the method further comprises:

after step D, taking the sum of the channel quality indication sequence number offset and the channel quality indication sequence number obtained in step D as the adjusted channel quality indication CQI_new。

22. The method of claim 21, wherein the adjusted Channel Quality Indication (CQI) is obtained_newAfter the step of (a), the method further comprises:

utilizing the CQI_newSearching a transmission block size table to obtain the size of a transmission block;

obtaining a correction code rate according to the size of the transmission block and the quantity of scheduling resources;

judging whether the correction code rate exceeds the code rate bearing upper limit of the AWGN channel or not,

when the judgment result is yes, carrying upper limit output according to the code rate of the AWGN channel;

and when the judgment result is negative, the correction code rate is kept unchanged.

23. The method of claim 15, wherein the block error rate segmentation window is a sliding window, the window length is W, the sliding step size is M, wherein W, M are positive integers, and M ≦ W.

24. The method of claim 23, wherein the adjustment of the cqi sequence number offset is made at the bler segment window boundary.

25. The method of claim 23, wherein the adjusting the cqi offset is performed within the bler segmentation window, and wherein the adjusting the cqi offset while within the window comprises:

judging whether a redundant cyclic check CRC window accumulated on a current subframe reaches a minimum CRC window or not;

and when the judgment result is yes, obtaining the block error rate, wherein the block error rate is the ratio of the number of errors of CRC in a CRC window accumulated on the current subframe to the length of the block error rate sectional counting window.

26. The method of claim 1, wherein the method further comprises:

selecting a modulation mode according to the code rate, the first modulation threshold and the second modulation threshold, wherein the first modulation threshold is smaller than the second modulation threshold,

when the code rate is smaller than the first modulation threshold, selecting a four-phase shift modulation mode QPSK;

when the code rate is between the first modulation threshold and the second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols;

and when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.

27. An apparatus for generating a channel quality indication, the apparatus comprising:

a signal-to-noise ratio change rule obtaining unit, configured to obtain a change rule of a signal-to-noise ratio of the channel according to a signal-to-noise ratio of a current subframe, that is, an nth subframe, received from the channel and signal-to-noise ratios of m subframes, received from the channel before the current subframe, where n and m are both natural numbers;

the signal-to-noise ratio predicted value obtaining unit is used for obtaining the signal-to-noise ratio predicted value of the (n + D) th subframe of the channel according to the change rule of the signal-to-noise ratio, wherein D is the number of delay subframes between the generation time of the channel quality indication and the effective time of the channel quality indication;

a code rate obtaining unit, configured to obtain a code rate corresponding to the predicted snr value according to a correspondence between the predicted snr value and the code rate;

a channel quality indication sequence number obtaining unit, configured to obtain a channel quality indication sequence number CQIindex according to the code rate and the number of scheduling resources of the channel;

the signal-to-noise ratio predicted value obtaining unit is specifically configured to:

counting a prediction success rate, wherein the prediction success rate is the probability that the signal-to-noise ratio is detected to continuously increase or continuously decrease in a prediction success rate counting window;

comparing the prediction success rate with a first power threshold Th1 and a second power threshold Th2, wherein the first power threshold is larger than the second power threshold,

when the prediction success rate is larger than the first success rate threshold value, a signal-to-noise ratio prediction value is obtained by utilizing a first prediction mode;

when the prediction success rate is smaller than the second power threshold value, a second prediction mode is selected and utilized to obtain a signal-to-noise ratio prediction value;

when the prediction success rate is between the first power-forming threshold value and the second power-forming threshold value, using the signal-to-noise ratio of the current sub-frame as a signal-to-noise ratio prediction value of the n + D sub-frame of the channel,

wherein Th1 is more than or equal to 0.3 and less than or equal to 0.5, and Th2 is more than or equal to 0.12 and less than or equal to 0.25;

wherein the first prediction mode is:

obtaining a weighted average of the SNR variations of adjacent subframes according to the SNR of the current subframe and m subframes before, and obtaining the SNR predicted value of the (n + D) th subframe according to the weighted average, or

Predicting the change speed of the signal-to-noise ratio from the signal-to-noise ratio of the current subframe to the signal-to-noise ratio of the (n + D) th subframe, and obtaining a signal-to-noise ratio predicted value of the (n + D) th subframe according to the change speed;

wherein the second prediction mode is:

taking the average value of the signal-to-noise ratios of the current sub-frame and the previous m sub-frames as the signal-to-noise ratio predicted value of the n + D sub-frame of the channel, or

And performing smooth filtering on the signal-to-noise ratios of the current subframe and the previous m subframes, and taking the obtained smooth value of the signal-to-noise ratio as a predicted value of the signal-to-noise ratio of the (n + D) th subframe of the channel.

28. The apparatus of claim 27, wherein the snr of the channel varies according to a random fluctuation of the snr or a continuous increase or a continuous decrease of the snr;

the signal-to-noise ratio predicted value obtaining unit comprises:

the signal-to-noise ratio prediction mode subunit is used for selecting a signal-to-noise ratio prediction mode corresponding to a change rule of the signal-to-noise ratio of the channel according to the change rule;

a first prediction sub-unit for obtaining a signal-to-noise ratio prediction value using a first prediction mode when the signal-to-noise ratio continuously increases or continuously decreases at a current sub-frame and m sub-frames before the current sub-frame,

and the second prediction subunit obtains the signal-to-noise ratio predicted value by using a second prediction mode when the signal-to-noise ratio fluctuates randomly between the current subframe and the previous subframe m.

29. The apparatus of claim 27, wherein the apparatus further comprises a CQI offset obtaining unit comprising:

the block error rate counting module is used for counting the CRC result of the channel demodulation in a block error rate segmentation window to obtain a block error rate;

a block error rate comparing module for comparing the block error rate with a first block error rate convergence threshold and a second block error rate convergence threshold, and adjusting the channel quality indication sequence number offset according to the comparison result, wherein the first block error rate convergence threshold is greater than the second block error rate convergence threshold,

when the block error rate is higher than the first block error rate convergence threshold, the current offset of the channel quality indication sequence number is adjusted downwards, and the block error rate in the block error rate segmentation window is counted again,

when the block error rate is lower than the second block error rate convergence threshold, the current offset of the channel quality indication sequence number is adjusted upwards, and the block error rate in the block error rate segmentation window is counted again,

when the block error rate is between the first block error rate convergence threshold and the second block error rate convergence threshold, keeping the channel quality indication sequence number offset unchanged,

the first block error rate convergence threshold is B_t*F_dThe second block error rate convergence threshold is B_t*F_uWherein B is_tAs a target value of block error rate, F_uIs a coefficient of rise, F is not less than 0_u≤1，F_dIs a coefficient of decrease, F is more than or equal to 1_dLess than or equal to 2, and F_u+F_d＝2。

30. The apparatus of claim 29, further comprising: a block error rate target value adjustment unit, the unit comprising:

a QOS grade requirement detection module for detecting the QOS grade requirement of the service;

and the block error rate target value obtaining module is used for searching the service block error rate target value adjusting table according to the detected QoS grade so as to obtain the block error rate corresponding to the QoS grade, and the block error rate is used as the block error rate target value aiming at the service.

31. The apparatus of claim 27, further comprising a modulation scheme selection unit,

the modulation mode selection unit is used for selecting a modulation mode according to the code rate, the first modulation threshold and the second modulation threshold, wherein the first modulation threshold is smaller than the second modulation threshold,

when the code rate is smaller than the first modulation threshold, selecting a four-phase shift modulation mode QPSK;

when the code rate is between the first modulation threshold and the second modulation threshold, selecting a quadrature amplitude modulation (16 QAM) mode containing 16 symbols;

and when the code rate is greater than the second modulation threshold, selecting a quadrature amplitude modulation (64 QAM) mode containing 64 symbols.