KR101940749B1 - Method for channel estimation and apparatus for thereof - Google Patents

Abstract

The present invention relates to a channel estimation method and, more specifically, to a channel estimation method and an apparatus therefor, capable of reducing an effect of frequency selective fading and reducing a data determination error at the same time to estimate a channel more accurately, by performing quadratic smoothing (QS) channel estimation on a pilot symbol and performing smoothing channel estimation on a data symbol. To this end, the channel estimation method according to an embodiment of the present invention comprises the following steps of: allowing a receiver to perform QS channel estimation by using a pilot symbol when a signal is received; allowing the receiver to perform equalization and demapping on a data symbol by using a channel estimation value estimated through the QS channel estimation; and allowing the receiver to perform smoothing channel estimation on the data symbol.

Description

[0001] METHOD FOR CHANNEL ESTIMATION AND APPARATUS FOR THEREOF [0002]

The present invention relates to a channel estimation method, and more particularly, to a quadratic smoothing (QS) channel estimation in a pilot symbol and a smoothing channel estimation in a data symbol, thereby reducing the influence of frequency selective fading, And more particularly, to a channel estimation method and an apparatus therefor.

Communication between people vs. objects and objects vs. objects, rather than communication between humans, has been presented as a variety of applications and scenarios for several years, some of which are being promoted by commercialization and standardization to some extent. Particularly, attention has recently been focused on V2X (Vehicle-to-Everything). V2X is a communication technology that provides information through wired and wireless networks around a vehicle, and can support various services related to vehicle communication such as traffic efficiency and autonomous driving. For example, if inter-vehicle communication is possible, information on dangerous road conditions, bad weather, and traffic congestion can be transmitted from one vehicle to another.

Such V2X communication can be classified into Vehicle-to-Vehicle (V2V), Vehicle-to-Pedestrian (V2P), and Vehicle-to-Infrastructure (V2I) communication. Among them, inter-vehicle communication, that is, V2V communication, relates to communication between vehicles traveling on the road, and information about the present traffic situation, road environment, and other vehicles' Thereby providing the driver with information on traffic congestion, safety accidents, and the like.

This V2V communication is very poor for signal propagation due to the following two factors. The first factor is that the time-varying characteristics of the channel are large due to the high mobility between vehicles. The second factor is that the channel frequency selective characteristics are very large due to multipath propagation due to multiple scattering between the vehicles. For this, a reliable channel estimation technique is needed in the V2V system.

Korean Registered Patent No. 10-1143242 Registered April 27, 2012 (Name: Channel Estimation for Wireless Communication)

SUMMARY OF THE INVENTION The present invention has been proposed in order to solve the above-mentioned problems of the prior art, and it is an object of the present invention to provide a quadratic smoothing (QS) channel estimation method in a pilot symbol for a channel that changes very rapidly with time, And a channel estimation method capable of correctly estimating a channel and an apparatus therefor.

It is another object of the present invention to provide a channel estimation method capable of obtaining a reliable channel by reducing a data determination error by performing a smoothing channel estimation on a data symbol and an apparatus therefor.

According to another aspect of the present invention, there is provided a channel estimation method, including: performing a Quadratic Smoothing (QS) channel estimation using a pilot symbol when a receiver receives a signal; Performing equalization and demapping on a data symbol using a channel estimation value estimated through the QS channel estimation; And performing smoothing channel estimation on the data symbols.

At this time, the QS channel estimation can be performed according to the following equation (13).

&Quot; (13) "

는 단위 행렬을 의미하며,

는 주파수 선택적 특성을 반영하는 인자이며,

는 송신된 파일럿 심볼이며,

는 수신된 파일럿 심볼을 의미하며,

는

행렬을 의미한다.At this time,

Denotes an identity matrix,

Is a factor that reflects frequency-selective characteristics,

Is the transmitted pilot symbol,

Denotes a received pilot symbol,

The

Matrix.

The performing the equalization and de-mapping comprises performing ZF (Zero Forcing) equalization using the channel estimation value estimated through the QS channel estimation and the received data symbol; And demapping the ZF-equalized data symbol to calculate a demapping data symbol.

The performing the smoothing channel estimation may include calculating a channel in a time domain according to a smoothing function including a diagonal matrix receiving the demapped data symbol as an input; And calculating a channel of the frequency domain region using the calculated channel of the time domain region.

In addition, after performing the smoothed channel estimation, in order to calculate an overall channel frequency response, if there is a next data symbol, a channel estimation value estimated through a smoothed channel estimation corresponding to the data symbol, Performing ZF equalization using a symbol; Calculating a demapping data symbol by demapping the ZF-equalized symbol; Calculating a channel estimation value for a next data symbol through LS (Least Square) channel estimation using the demapping data symbol; And performing smoothing channel estimation on the demapped data symbols.

Further, the present invention can provide a computer readable recording medium on which a program for executing the channel estimation method as described above is recorded.

According to an aspect of the present invention, there is provided a receiver including: a signal transmission / reception unit for receiving a signal from a transmitter; And performing QS (Quadratic Smoothing) channel estimation using the pilot symbols of the received signal and performing equalization and demapping on the data symbols of the received signal using the channel estimation value estimated through the QS channel estimation And a signal processor for performing smoothing channel estimation on the data symbols.

In this case, in order to calculate an overall channel frequency response, the signal processing unit may perform equalization and de-interleaving using a channel estimation value estimated through smoothing channel estimation and a received next data symbol corresponding to the data symbol, Performs a mapping on the next data symbol, calculates a channel estimation value for a next data symbol through Least Square (LS) channel estimation using the demapped data symbol of the next data, and performs a smoothing channel estimation on the next data symbol .

 5G and B5G systems, and vehicle communication, the proposed channel estimation scheme can achieve higher performance gain compared with the channel estimation scheme used in existing mobile communication systems.

This improves the performance of Prediction MSE (Mean Square Error) and BER (Bit Error Rate) through improvement of Signal to Noise Ration (SNR) performance showing improvement of QoS of users.

Also, if the present invention is successfully applied to the 5G and B5G systems, it can be a preemptive technology in a vehicle environment, reliable data detection can be performed through accurate channel estimation, and a safety effect can be obtained in vehicle communication.

As described above, the main core technologies of the present invention can bring about academic ripple effects and securing prior arts for national research and development.

1 is an exemplary diagram for explaining the position of a DMRS in a subframe.
2 is an exemplary diagram for explaining a channel estimation method according to the LS scheme.
3 is an exemplary diagram for explaining a channel estimation method according to the DDCE scheme.
4 is an exemplary diagram for explaining a channel estimation method according to the STA scheme.
5 is an exemplary diagram for explaining a channel estimation method according to a smoothing method.
FIG. 6 is a flowchart for schematically explaining a channel estimation method according to an embodiment of the present invention.
7 is a diagram for explaining the channel estimation method according to an embodiment of the present invention in more detail.
8 is a diagram illustrating a structure of a receiver according to an embodiment of the present invention.
9 to 12 are diagrams showing the effect of the channel estimation method according to the embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS For a more complete understanding of the nature and advantages of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings, in which:

In the following description and the accompanying drawings, detailed description of well-known functions or constructions that may obscure the subject matter of the present invention will be omitted. It should be noted that the same constituent elements are denoted by the same reference numerals as possible throughout the drawings.

The terms and words used in the following description and drawings are not to be construed in an ordinary sense or a dictionary, and the inventor can properly define his or her invention as a concept of a term to be described in the best way It should be construed as meaning and concept consistent with the technical idea of the present invention. Therefore, the embodiments described in the present specification and the configurations shown in the drawings are merely the most preferred embodiments of the present invention, and not all of the technical ideas of the present invention are described. Therefore, It is to be understood that equivalents and modifications are possible.

Also, terms including ordinal numbers such as first, second, etc. are used to describe various elements, and are used only for the purpose of distinguishing one element from another, Not used. For example, without departing from the scope of the present invention, the second component may be referred to as a first component, and similarly, the first component may also be referred to as a second component.

In addition, when referring to an element as being "connected" or "connected" to another element, it means that it can be connected or connected logically or physically. In other words, it is to be understood that although an element may be directly connected or connected to another element, there may be other elements in between, or indirectly connected or connected.

Also, the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise. It is also to be understood that the terms such as " comprising "or" having ", as used herein, are intended to specify the presence of stated features, integers, It should be understood that the foregoing does not preclude the presence or addition of other features, numbers, steps, operations, elements, parts, or combinations thereof.

In addition, embodiments within the scope of the present invention include computer-readable media having computer-executable instructions or data structures stored on computer-readable media. Such computer-readable media can be any available media that is accessible by a general purpose or special purpose computer system. By way of example, and not limitation, such computer-readable media can comprise RAM, ROM, EPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or in the form of computer- But is not limited to, a physical storage medium such as any other medium that can be used to store or communicate certain program code means of the general purpose or special purpose computer system, .

In the following description and claims, the term "network" is defined as one or more data links that enable electronic data to be transmitted between computer systems and / or modules. When the information is transmitted or provided to a computer system via a network or other (wired, wireless, or a combination of wired or wireless) communication connection, the connection may be understood as a computer-readable medium. Computer readable instructions include, for example, instructions and data that cause a general purpose computer system or special purpose computer system to perform a particular function or group of functions. The computer executable instructions may be binary, intermediate format instructions, such as, for example, assembly language, or even source code.

In addition, the invention may be practiced with other computer systems, including personal computers, laptop computers, handheld devices, multiprocessor systems, microprocessor-based or programmable consumer electronics, network PCs, minicomputers, mainframe computers, a pager, and the like. < RTI ID = 0.0 > [0040] < / RTI > The invention may also be practiced in distributed systems environments where both local and remote computer systems linked by a combination of wired data links, wireless data links, or wired and wireless data links over a network perform tasks. In a distributed system environment, program modules may be located in local and remote memory storage devices.

Now, a channel estimation method and an apparatus therefor according to an embodiment of the present invention will be described in detail with reference to the drawings. Here, the same reference numerals are used for similar functions and functions throughout the drawings, and a duplicate description thereof will be omitted.

Hereinafter, a system to which a channel estimation method according to an embodiment of the present invention is applied will be described.

The embodiment of the present invention can be performed on an LTE based uplink system of 3GPP (3rd Generation Partnership Project).

The LTE-based uplink system of the 3rd Generation Partnership Project (3GPP) uses a DFT-spreading SC-FDMA (Orthogonal Frequency Division Multiple Access) scheme to reduce the high peak to average power ratio (PAPR) of OFDMA Single Carrier-Frequency Division Multiple Access).

In this LTE based uplink system, channel estimation according to an embodiment of the present invention performs channel estimation based on pilot symbols. At this time, the pilot symbol uses a demodulation reference signal (DMRS), and the DMRS is a training signal known to both the transmitting and receiving end.

Hereinafter, the demodulation reference signal DMRS in the V2I communication system model of the present invention will be described.

1 is an exemplary diagram for explaining the position of a DMRS in a subframe.

In general, the basic unit of data transmission is a subframe unit of a radio frame. A radio frame is composed of 10 subframes, and one subframe is composed of two slots (solots). At this time, the number of OFDM symbols included in one slot may vary according to a cyclic prefix (CP). Here, CP is a signal inserted in a guard interval in order to remove inter-symbol interference due to multipath in an OFDM transmission scheme. The CP is an extended CP and a normal CP, . ≪ / RTI > For example, when an OFDM symbol is configured by a general CP, the number of OFDM symbols included in one slot is 7, and one subframe is composed of 2 symbols. Therefore, a total of 14 OFDM symbols ≪ / RTI > The demodulation reference signal DMRS is located at the fourth and eleventh OFDM symbols of the time-frequency resource grid.

The signal received in the OFDM system is expressed by Equation (1) below.

는 수신된 파일럿 심볼,

는 송신된 파일럿 심볼,

는 채널 계수, 그리고

는 가우시안 잡음을 의미한다.

는 각각 OFDM 심볼과 부반송파 인덱스를 나타낸다. here,

Received pilot symbols,

≪ / RTI > is the transmitted pilot symbol,

Is the channel coefficient, and

Means Gaussian noise.

Represents an OFDM symbol and a subcarrier index, respectively.

Before describing a channel estimation method according to an embodiment of the present invention, a channel estimation method according to the related art will be described first.

The conventional channel estimation methods are LS (Least Square), DDCE (Decision Directed Channel Estimation), STA (Spectral Temporal Averaging) and Smoothing techniques.

First, a channel estimation method according to the LS scheme will be described.

2, an LS channel estimation method in step S101 is a method for estimating a pilot symbol transmitted from a received pilot symbol in each slot, as shown in FIG. 2, It can be calculated by giving. That is, the LS channel estimation method can be defined according to Equation (2) below.

는 추정된 채널이며,

는 수신한 파일럿 심볼,

는 송신한 파일럿 심볼을 의미한다. here,

Is an estimated channel,

Received pilot symbols,

Denotes a transmitted pilot symbol.

Hereinafter, a channel estimation method according to the DDCE method will be described.

DDCE is a decision-directed channel estimation method, and is a channel estimation method that is mainly used in a channel that changes slowly in time. The DDCE estimates the channel using the estimated transmission signal by using the highly correlated intersymbol data to show a high gain in a frequency non-selective environment.

This will be described with reference to FIG.

FIG. 3 illustrates an example of a channel estimation method according to the DDCE scheme. As shown in FIG. 3, the DDCE scheme estimates a channel by using a data signal as a pilot symbol.

First, the initial LS estimation step is performed in step S201. In step S203, the first data symbol received is equalized using the channel estimated by the LS in step S201. In this case, the LS estimation process in step S201 is the same as that in Equation (2), and the equalization process using the channel estimated by the initial LS in step S203 can be defined according to Equation (3) .

는 등화한 심볼을 의미하며,

는 수신한 데이터 심볼,

는 이전 심볼에서 추정한 채널 그리고

는 LS로부터 얻어진 초기 추정 채널이다. here,

Quot; means an equalized symbol,

The received data symbol,

Is the channel estimated from the previous symbol and

Is an initial estimated channel obtained from LS.

을 디매핑하여

를 구하게 된다. 디매핑을 통해

를 산출하는 과정은 하기의 <수학식 4>에 따라 정의될 수 있다. In order to estimate the channel, in step S205,

By demapping

. Through demapping

Can be defined according to Equation (4) below.

는 디매핑을 의미한다. In Equation (4)

Means demapping.

를 이용하여 하기의 <수학식 5>에 따라 LS 채널 추정 과정을 통해 다음 채널을 추정하게 된다. Thereafter, in step S207

To estimate the next channel through the LS channel estimation process according to Equation (5) below.

This DDCE technique has a disadvantage of error propagation due to erroneous decision in case of low SNR.

Hereinafter, a channel estimation method according to a STA (Spectral Temporal Averaging) method will be described.

FIG. 4 is a diagram for explaining a channel estimation method according to the STA scheme. As shown in FIG. 4, the STA scheme calculates an average in a frequency domain and a time domain using a channel estimation value using a data pilot symbol.

을 산출하게 된다. 이에 대한 과정은 LS 방식의 <수학식 2>와 DDCE 방식의 <수학식 3>에서 정의한 바와 같다. The first data symbol received in step S303 is equalized using the channel estimated as the initial LS in step S301

. The procedure for this is as defined in Equation (2) of LS method and Equation (3) of DDCE method.

을 디매핑하여

를 구하하고, 이를 이용하여 S307 단계에서 LS 채널 추정으로 다음 채널을 추정하게 된다. 이에 대한 과정은 DDCE 방식을 통해 설명한 <수학식 4> ~ <수학식 5>에서 정의한 바와 같다. In order to estimate the channel, in step S305,

By demapping

And estimates the next channel using the LS channel estimation in step S307. The procedure for this is as defined in Equation (4) to Equation (5) described through the DDCE method.

Then, the average is calculated in the frequency domain of the channel estimated in step S309. The average in the frequency domain can be calculated according to Equation (6) below.

은 가중치 계수로

이다. Where s is a value indicating a subcarrier region to be averaged in the frequency domain,

Lt; RTI ID = 0.0 &gt;

to be.

After calculating the average in the frequency domain, the average in the time domain is calculated in step S311. The average in the time domain can be calculated according to Equation (7) below.

는 업데이트 변수로

의 값을 가진다.

값이 크면 시불변 채널에 적합하고 작으면 시변 채널에 적합하다. 또한 s값이 크면 평탄 페이딩 채널에 적합하고, 작으면 주파수 선택적 페이딩 채널에 적합하다. here,

Is an update variable.

Lt; / RTI &gt;

If the value is large, it is suitable for the time constant channel, and if it is small, it is suitable for the time varying channel. Also, a large s value is suitable for a flat fading channel, while a small value is suitable for a frequency selective fading channel.

Hereinafter, the smoothing technique will be described.

Smoothing means a method by which a part of the estimated noise can be removed by using the radio propagation characteristics.

This smoothing method will be described with reference to FIG.

5, the smoothing scheme reduces the maximum value of the data determination error, thereby achieving a low SNR (Signal to Noise Ratio) when combined with the DDCE scheme. [0053] FIG. 5 is a diagram for explaining a channel estimation method according to the smoothing scheme. Performance can be shown.

To describe more specifically the smoothing technique, first, a pilot symbol is defined according to Equation (8) below.

는 파일럿 심볼을 입력으로 받는 대각 행렬이며, F는 FFT(Fast Fourier Transform) 행렬을 의미한다. 그리고

는 시간 영역에서의 채널을 의미하며,

는 잡음을 의미한다.

는 K의 길이에 맞게 축소된 FFT 행렬이며, F 행렬로부터 K의 열을 선택한 것이다. 또한

도 K의 길이에 맞게 축소된 시간영역 채널이며,

로부터 K의 열을 선택한 것이다.here,

Denotes a diagonal matrix for receiving pilot symbols as input, and F denotes a Fast Fourier Transform (FFT) matrix. And

Denotes a channel in the time domain,

Means noise.

Is an FFT matrix that is reduced to fit the length of K, and the column of K is selected from the F matrix. Also

Is a time-domain channel reduced to fit the length of K,

I have chosen the column K from.

를 산출하게 된다. 이에 대한 과정은 앞서 설명한 <수학식 2>와 <수학식 3>에 따라 정의될 수 있다. First, the first data symbol received in step S403 is equalized using the channel estimated as the initial LS in step S401

. The process for this can be defined according to Equation (2) and Equation (3) described above.

를 디매핑하여

를 구하고 이를 이용해서 S407 단계에서 LS 채널 추정으로 다음 채널을 추정하게 된다. 이에 대한 과정은 앞서 설명한 <수학식 4> ~ <수학식 5>에 따라 정의될 수 있다. In order to estimate the channel, in step S405,

By demapping

And estimates the next channel using the LS channel estimation in step S407. The process for this can be defined according to Equations (4) to (5).

는 하기의 <수학식 9>와 같다. In step S409, the channel is estimated in the time domain.

Is expressed by Equation (9) below.

은 곱을 의미한다. Where the sign + signifies a pseudoinverse,

Means the product.

는 시간 영역에서 추정된 채널

로부터 하기의 <수학식 10>에 따라 산출될 수 있다. In step S411, a channel is estimated in the frequency domain. In the frequency domain,

Lt; RTI ID = 0.0 &gt;

Can be calculated from Equation (10) below.

Hereinafter, a channel estimation method according to an embodiment of the present invention will be described. For convenience of description, the channel estimation method according to an embodiment of the present invention may be referred to as ASCE technique.

6 is a flowchart for schematically explaining a channel estimation method according to an embodiment of the present invention.

Referring to FIG. 6, a channel estimation method according to an embodiment of the present invention may be performed by a receiver, and a channel estimation process may be performed by receiving a signal from a transmitter (S501). At this time, the received signal may include pilot symbols and data symbols. In the present invention, a channel is estimated using a data symbol together with a pilot symbol which is a short reference signal for a very rapidly changing channel.

To this end, the receiver estimates the QS channel for the pilot symbol in the received signal (S503). And estimates a channel by taking a smoothing scheme in a data symbol using a channel estimation value estimated for a QS channel. That is, the equalization and demapping process for the data symbols is performed using the channel estimation value estimated for the QS channel (S505), and the channel is estimated according to the smoothing scheme (S507). Equalization, demapping, and smoothing channel estimation for data symbols may be performed repeatedly until all channel frequency responses are obtained for all data symbols (S509).

Through this process, the present invention can reduce the error of the initial channel estimation by reducing the effect of frequency selective fading by performing channel estimation with QS, and estimating the channel using a smoothing method in the data symbol, . &Lt; / RTI &gt;

A channel estimation method according to an embodiment of the present invention will be described in more detail with reference to FIG.

7 is a diagram for explaining the channel estimation method according to an embodiment of the present invention in more detail.

Referring to FIG. 7, a QS channel for a pilot symbol is estimated in step S601. The QS method can be expressed mathematically on the basis of convex minimization and it is possible to reduce the error of channel estimation by reducing the effect of frequency selective fading. Therefore, the QS channel is estimated using pilot symbols known to both the transmitting and receiving end. The QS method can be expressed as a convex minimization problem by Equation (11) below.

Here, d is a factor reflecting the frequency-selective characteristic, and the Q matrix can be expressed as Equation (12).

As a result, the channel estimation through the QS technique is expressed by Equation (13).

Where I represents a unit matrix.

를 이용하여 데이터 심볼에 대한 ZF(Zero Forcing) 등화를 수행한다. 등화를 통해 얻은 심볼

은 하기의 <수학식 14>와 같이 나타낼 수 있다. Thereafter, the present invention performs ZF equalization on the data symbols (S603). That is, according to the present invention, a channel estimated by a QS scheme corresponding to a pilot symbol

To perform Zero Forcing (ZF) equalization on the data symbols. Symbol obtained through equalization

Can be expressed by Equation (14) below.

심볼을 디매핑하여

심볼을 얻는다(S605). At this time, as shown in Equation (15) below,

By demapping the symbol

Symbols are obtained (S605).

Here, the symbol Q means demapping.

은 하기의 <수학식 16>과 같다. Thereafter, the present invention performs smoothing channel estimation using data symbols. At this time, the channel is estimated in the time domain (S607). Estimated channel in time domain

Is expressed by Equation (16) below.

는 데이터 심볼을 입력으로 받는 대각 행렬이며, F는 FFT 행렬을 의미한다. 그리고

는 시간 영역 채널이며,

는 가우시안 잡음이다.

는 K의 길이에 맞게 축소된 FFT 행렬이며, F 행렬로부터 K의 열을 선택한 것이다. 또한

도 K의 길이에 맞게 축소된 시간영역 채널이며,

로부터 K의 열을 선택한 것이다. 여기서 기호 +와

은 각각 의사역행렬과 곱을 의미한다. here

Is a diagonal matrix that receives data symbols as inputs, and F denotes an FFT matrix. And

Is a time-domain channel,

Is Gaussian noise.

Is an FFT matrix that is reduced to fit the length of K, and the column of K is selected from the F matrix. Also

Is a time-domain channel reduced to fit the length of K,

I have chosen the column K from. Here,

Denotes the product of the pseudo-inverse and the product, respectively.

로부터 주파수 영역에서의 채널을 추정할 수 있으며(S609), 주파수 영역에서의 추정된 채널

은 하기의 <수학식 17>의 정의에 따라 산출될 수 있다. Then, in the time domain,

(S609), and estimates the channel in the frequency domain

Can be calculated according to the definition of Equation (17) below.

Hereinafter, the feedback process will be described.

를 산출하게 되며, 하기의 <수학식 18>에 따라 정의된다. Then, the channel of the next symbol is obtained using the channel estimated from the symbol of the previous step. First, the data symbols are equalized again to obtain the channel of the next symbol (S611)

And is defined according to Equation (18) below.

심볼을 디매핑하여

심볼을 얻는다(S613). At this time, as shown in Equation (19) below,

By demapping the symbol

Symbols are obtained (S613).

Here, the symbol Q means demapping.

In addition, the present invention estimates the next channel by applying the LS channel estimation scheme as defined in Equation (19) (S615).

Thereafter, the smoothing channel estimation is performed for the time domain and the frequency domain using the data symbols (S617 to S619), and the process is as shown in Equations (16) to (17).

Then, the feedback process is repeated until the entire channel frequency response is obtained.

The channel estimation method according to the embodiment of the present invention has been described above.

The channel estimation method according to the embodiment of the present invention can be performed by a receiver that receives a signal as described above. The receiver of the present invention will be briefly described with reference to Fig.

8 is a diagram illustrating a structure of a receiver according to an embodiment of the present invention.

Referring to FIG. 8, the receiver 100 of the present invention may include a signal transmission / reception unit 110 and a signal processing unit 120.

First, the signal transmitting and receiving unit 110 receives a signal including pilot symbols and data symbols, and transmits the signal to the signal processing unit 120.

6 and 7, the signal processing unit 120 estimates a QS channel for a pilot symbol of a received signal, and estimates a QS channel for a data symbol using a channel estimation value estimated through QS channel estimation Performs equalization and demapping, and estimates a smoothing channel for a data symbol.

The channel estimation method and the apparatus therefor according to the embodiment of the present invention have been described above.

Hereinafter, simulation results and performance according to the embodiment of the present invention will be described.

The simulation of the present invention is based on an LTE based uplink system. At this time, the relationship between the speed and the Doppler frequency is as follows.

Urban Highway Vehicle velocity 15 km / h 140 km / h Relative velocity 30 km / h 280 km / h Doppler frequency 166 Hz 1555Hz

The system parameters are shown in Table 2 below.

Parameter Value Carrier frequency 6GHz Bandwidth 10Mhz Sample frequency 15.36 MHz Subframe duration 1ms Subcarrier spacing 15kHz FFT size 1024 Occupied subcarriers 600 No. of subcarriers / PRB 12 Cyclic Prefix (CP) Normal CP No. of OFDM symblos / subframe 14 (Normal CP) Modulation scheme QPSK Noise AWGN f, s 2.2 K 150 d 8 Velocity Urban 15 km / h, f_D = 166 Hz
Highway: 140km / h ,, f_D = 1555Hz Channel Model Urban: UMi_LoS
Highway: UMa_NLoS MIMO Configuration 1x1 Channel Estimation DDCE, STA, Smoothing, ASCE Advanced Receiver ZF

9 and 12 illustrate the effect of the channel estimation method according to an embodiment of the present invention. First, FIG. 9 and FIG. 10 illustrate an example of a normalized mean square error (NMSE) and a bit error rate (BER) Respectively. As can be seen from FIG. 9, performance is improved in the order of DDCE, STA, Smoothing, and the proposed ASCE. In case of low SNR, DDCE generates error propagation due to wrong decision and shows good performance at high SNR. STA is based on DDCE and has better performance than DDCE because it takes average in frequency domain and time domain. In the case of smoothing, it shows good performance by reducing the maximum value of data decision error. However, it can be seen that the ASCE, which is an embodiment of the present invention, has better performance than the existing channel estimation techniques at low SNR and high SNR.

11 and 12 are views showing NMSE and BER on a highway. As in the case of urban areas, DDCE, STA, Smoothing, and ASCE, the proposed technique, are superior in performance.

The channel estimation method according to the embodiment of the present invention has been described above.

The channel estimation method according to an embodiment of the present invention as described above may be provided in the form of a computer readable medium suitable for storing computer program instructions and data.

At this time, the program recorded on the recording medium can be read and installed in the computer and executed, thereby executing the above-described functions.

In order to allow a computer to read a program recorded on a recording medium and to execute functions implemented by the program, the above-mentioned program may be stored in a computer-readable medium such as C, C ++, JAVA, machine language, and the like.

The code may include a function code related to a function or the like that defines the functions described above and may include an execution procedure related control code necessary for the processor of the computer to execute the functions described above according to a predetermined procedure. In addition, such code may further include memory reference related code as to what additional information or media needed to cause the processor of the computer to execute the aforementioned functions should be referenced at any location (address) of the internal or external memory of the computer . In addition, when a processor of a computer needs to communicate with any other computer or server that is remote to execute the above-described functions, the code may be stored in a memory of the computer using a communication module of the computer, It may further include a communication-related code such as how to communicate with another computer or a server, and what information or media should be transmitted or received during communication.

Such computer-readable media suitable for storing computer program instructions and data include, for example, magnetic media such as hard disks, floppy disks and magnetic tape, compact disk read only memory (CD-ROM) Optical media such as a DVD (Digital Video Disk), a magneto-optical medium such as a floppy disk, and a ROM (Read Only Memory), a RAM , Random Access Memory), flash memory, EPROM (Erasable Programmable ROM), and EEPROM (Electrically Erasable Programmable ROM). The processor and memory may be supplemented by, or incorporated in, special purpose logic circuits.

The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner. The functional program for implementing the present invention and the related code and code segment may be implemented by programmers in the technical field of the present invention in consideration of the system environment of the computer that reads the recording medium and executes the program, Or may be easily modified or modified by the user.

Each step according to the embodiments of the present invention can be implemented by a computer system and implemented by computer-executable instructions. As used herein, a "computing system" is defined as one or more software modules, one or more hardware modules, or a combination thereof that operate in conjunction with performing an operation on electronic data. For example, the definition of a computer system includes a software module such as a personal computer's operating system and a hardware component of a personal computer. The physical layout of the module is not important. The computer system may include one or more computers connected through a network.

Likewise, a computing system may be implemented in a single physical device in which an internal module, such as a memory and a processor, operates in conjunction with performing an operation on the electronic data.

Also, as described above, the present specification contains details of a number of specific implementations, but they should not be construed as being limitations on the scope of any invention or claim, but rather on the particular embodiment of a particular invention But should be understood as an explanation of certain features. Certain features described herein in the context of separate embodiments may be implemented in combination in a single embodiment. Conversely, various features described in the context of a single embodiment may also be implemented in multiple embodiments, either individually or in any suitable subcombination. Further, although the features may operate in a particular combination and may be initially described as so claimed, one or more features from the claimed combination may in some cases be excluded from the combination, Or a variant of a subcombination.

Likewise, although the operations are depicted in the drawings in a particular order, it should be understood that such operations must be performed in that particular order or sequential order shown to achieve the desired result, or that all illustrated operations should be performed. In certain cases, multitasking and parallel processing may be advantageous. Also, the separation of the various system components of the above-described embodiments should not be understood as requiring such separation in all embodiments, and the described program components and systems will generally be integrated together into a single software product or packaged into multiple software products It should be understood.

Certain embodiments of the subject matter described herein have been described. Other embodiments are within the scope of the following claims. For example, the operations recited in the claims may be performed in a different order and still achieve desirable results. By way of example, the process illustrated in the accompanying drawings does not necessarily require that particular illustrated or sequential order to obtain the desired results. In certain implementations, multitasking and parallel processing may be advantageous.

The description sets forth the best mode of the invention, and is provided to illustrate the invention and to enable those skilled in the art to make and use the invention. The written description is not intended to limit the invention to the specific terminology presented. Thus, while the present invention has been described in detail with reference to the above examples, those skilled in the art will be able to make adaptations, modifications, and variations on these examples without departing from the scope of the present invention.

Therefore, the scope of the present invention should not be limited by the described embodiments but should be defined by the claims.

The next generation mobile communication core technology obtained through the present invention is expected to contribute not only to enhancement of mobile communication performance but also to export of terminal parts and network construction. In addition, reliable data detection can have a significant impact on the vehicle communications market. Specifically, it will contribute to securing superiority in standardization competition and leading the next generation mobile communication market. It will improve technology self-reliance and price competitiveness of domestic mobile communication industry through transfer of intellectual property rights such as patents related to next generation mobile communication, In addition to reducing the cost of mobile communication industry due to cross-licensing, it is anticipated to reduce royalty payment and import substitution effect by securing core technology of next generation mobile communication.

In addition, since the present invention is not only possible to be marketed or operated, but also can be practically and practically carried out, it is industrially applicable.

100: receiver
110: Signal transmission /
120: Signal processor

Claims (8)

The receiver,
Performing a Quadratic Smoothing (QS) channel estimation using a pilot symbol when a signal is received;
Performing equalization and demapping on a data symbol using a channel estimation value estimated through the QS channel estimation; And
Performing smoothing channel estimation on the data symbols,
The step of performing equalization and demapping comprises:
Performing ZF (Zero Forcing) equalization using a channel estimation value estimated through the QS channel estimation and a received data symbol; And
Calculating a demapping data symbol by demapping the ZF equalized data symbol;
Wherein the channel estimating method comprises: The method according to claim 1,
Wherein the QS channel estimation is performed according to Equation (13).
&Quot; (13) &quot;

At this time,

Denotes an identity matrix,

Is a factor that reflects frequency-selective characteristics,

Is the transmitted pilot symbol,

Denotes a received pilot symbol,

The

Means matrix delete The method according to claim 1,
Wherein performing the smoothed channel estimation comprises:
Calculating a channel in a time domain according to a smoothing function including a diagonal matrix receiving the demapped data symbol as an input; And
Calculating a channel of the frequency domain region using the calculated channel of the time domain region;
Wherein the channel estimating method comprises: The method according to claim 1,
After performing the smoothed channel estimation,
To produce the full channel frequency response, if there is a next data symbol,
Performing ZF equalization using a channel estimation value estimated through smoothing channel estimation corresponding to the data symbol and a received next data symbol;
Calculating a demapping data symbol by demapping the ZF-equalized symbol;
Calculating a channel estimation value for a next data symbol through LS (Least Square) channel estimation using the demapping data symbol; And
Performing smoothing channel estimation on the demapped data symbols;
Wherein the channel estimating method comprises: A program for executing the channel estimation method according to any one of claims 1, 2, 4, and 5. A signal transmitting / receiving unit for receiving a signal from a transmitter; And
Performs Quadratic Smoothing (QS) channel estimation using the pilot symbols of the received signal, and performs equalization and demapping on the data symbols of the received signal using the channel estimation values estimated through the QS channel estimation And a signal processor for performing smoothing channel estimation on the data symbols,
The signal processing unit,
Performing ZF (Zero Forcing) equalization using the channel estimation value estimated by the QS channel estimation and the received data symbol, and demodulating the ZF equalized data symbol to calculate a demapping data symbol Characterized by a receiver. 8. The method of claim 7,
The signal processing unit
And performs equalization and demapping using a channel estimation value estimated through smoothing channel estimation and a next data symbol received, corresponding to the data symbol, if the next data symbol is present, to calculate a full channel frequency response, Calculating channel estimation values for a next data symbol through LS (Least Square) channel estimation using demapped data symbols of the next data, and performing smoothing channel estimation on the next data symbol.

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