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WO2024174830A1 - 速率预测方法、电子设备及计算机可读存储介质 - Google Patents

速率预测方法、电子设备及计算机可读存储介质 Download PDF

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Publication number
WO2024174830A1
WO2024174830A1 PCT/CN2024/075204 CN2024075204W WO2024174830A1 WO 2024174830 A1 WO2024174830 A1 WO 2024174830A1 CN 2024075204 W CN2024075204 W CN 2024075204W WO 2024174830 A1 WO2024174830 A1 WO 2024174830A1
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WIPO (PCT)
Prior art keywords
neighboring cell
downlink
target
rate
user account
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PCT/CN2024/075204
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English (en)
French (fr)
Inventor
高超
牛康
Original Assignee
中兴通讯股份有限公司
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Publication of WO2024174830A1 publication Critical patent/WO2024174830A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements
    • H04W36/0005—Control or signalling for completing the hand-off
    • H04W36/0083—Determination of parameters used for hand-off, e.g. generation or modification of neighbour cell lists
    • H04W36/0085—Hand-off measurements
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/142—Network analysis or design using statistical or mathematical methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L41/00—Arrangements for maintenance, administration or management of data switching networks, e.g. of packet switching networks
    • H04L41/14—Network analysis or design
    • H04L41/147—Network analysis or design for predicting network behaviour
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L43/00—Arrangements for monitoring or testing data switching networks
    • H04L43/08—Monitoring or testing based on specific metrics, e.g. QoS, energy consumption or environmental parameters
    • H04L43/0876—Network utilisation, e.g. volume of load or congestion level
    • H04L43/0894—Packet rate
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W24/00—Supervisory, monitoring or testing arrangements
    • H04W24/08—Testing, supervising or monitoring using real traffic
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W36/00—Hand-off or reselection arrangements

Definitions

  • the present application relates to the field of communication technology, and in particular to a rate prediction method, an electronic device, and a computer-readable storage medium.
  • RSRP Reference Signal Receiving Power
  • RSRQ Reference Signal Receiving Quality
  • SINR Signal to Interference plus Noise Ratio
  • the main purpose of this application is to provide a rate prediction method, an electronic device and a computer-sustainable storage medium, aiming to solve the technical problem of how to improve the accuracy of neighboring cell downlink perception rate prediction.
  • the present application provides a rate prediction method, which is applied to a serving cell, comprising:
  • Obtain a neighboring cell fingerprint library sent by a target neighboring cell wherein the neighboring cell fingerprint library is divided into grids according to user information of historical user accounts, and downlink spectrum efficiency corresponding to user information belonging to the same grid is counted, and the downlink spectrum efficiency is added to the corresponding grid to generate;
  • the present application also provides a rate prediction method, which is applied to a target neighboring area, including:
  • the neighboring cell fingerprint library is sent to a serving cell, and the serving cell determines a neighboring cell downlink perception rate of the target user account in the target neighboring cell based on the neighboring cell fingerprint library.
  • the present application also provides a rate prediction method, which is applied to a base station, including:
  • the present application also provides an electronic device, which includes: a memory, a processor, and a rate prediction program stored in the above-mentioned memory and executable on the above-mentioned processor, and when the above-mentioned rate prediction program is executed by the above-mentioned processor, the steps of the rate prediction method as described above are implemented.
  • the present application also provides a computer-readable storage medium, on which a rate prediction program is stored.
  • a rate prediction program is stored on which a rate prediction program is stored.
  • FIG1 is a schematic diagram of a flow chart of a first embodiment of a rate prediction method of the present application
  • FIG2 is a schematic diagram of a flow chart of a second embodiment of a rate prediction method of the present application.
  • FIG3 is a schematic diagram of a flow chart of a third embodiment of a rate prediction method of the present application.
  • FIG4 is a schematic diagram of a flow chart of a fourth embodiment of a rate prediction method of the present application.
  • FIG5 is a schematic diagram of a module of a rate prediction system in the rate prediction method of the present application.
  • FIG6 is a schematic diagram of the device structure of the hardware operating environment involved in the rate prediction method in an embodiment of the present application.
  • the network side needs to monitor the user's service quality in real time to ensure the user's optimal perceived experience.
  • the base station evaluates whether the user needs to trigger switching by monitoring the RSRP (Reference Signal Receiving Power), RSRQ (Reference Signal Receiving Quality), and SINR (Signal to Interference plus Noise Ratio) values of the terminal in the service cell and the neighboring cell.
  • the neighboring cells are also selected based on RSRP, RSRQ, and SINR.
  • RSRP, RSRQ, and SINR can only reflect the quality of the downlink channel, and cannot fully reflect the user's downlink perception experience, resulting in low accuracy in the prediction of the downlink perception rate of the neighboring cell.
  • the downlink perception rate of the user in the neighboring cell is predicted in advance, so that the neighboring cell can be selected based on the perception rate during the switching process to ensure that the user is always in a cell with the best downlink perception.
  • the demand for downlink rate is relatively large.
  • the neighboring cell with the largest downlink perception rate can be selected for the user based on the downlink perception rate.
  • SE downlink spectral efficiency
  • the average downlink SE of the neighboring cell can only reflect the average level of the neighboring cell, and cannot represent the actual situation of a specific user. Therefore, there will be a large error in the rate prediction using the average downlink SE of the neighboring cell. Therefore, in this embodiment, the neighboring cell fingerprint library can be used to predict the downlink SE of the neighboring cell to improve the accuracy of the prediction of the downlink perceived rate of the neighboring cell.
  • the downlink perceived rate of the user in the neighboring cell can be evaluated, which can be applied in the communication system.
  • the mobility process of the communication system such as switching, PSCell (Primary Secondary Cell) change, SN (Secondary Node) addition/change, CA (Carrier Aggregatio) auxiliary carrier addition/change
  • the downlink perceived rate of the user in the neighboring cell can be estimated, and a cell with the best downlink perceived rate can be selected for the user.
  • It is also possible to construct an SE grid by associating some indicators that are strongly related to SE with the scheduling SE of historical users. Before switching, the values of these indicators that are strongly related to SE are obtained from the neighboring cell, and then the SE grid is queried to obtain the SE information of the neighboring cell.
  • the present application provides a rate prediction method.
  • the rate prediction method is applied to a serving cell, including:
  • Step S10 obtaining a neighboring cell fingerprint library sent by a target neighboring cell, wherein the neighboring cell fingerprint library is grid-divided according to user information of historical user accounts, and the downlink spectrum efficiency corresponding to the user information in the same grid is counted, and the downlink spectrum efficiency is added to the corresponding grid to generate;
  • the terminal used by the user may move from the coverage of the current serving cell to the coverage of another cell.
  • the wireless signal quality of the UE serving cell is poor, it is usually necessary to switch the UE to a neighboring cell (i.e., neighboring cell) with better wireless signal quality. This process is called handover.
  • the method in this embodiment can be used to estimate the downlink perception rate of the target user account corresponding to the terminal held by the user in different cells, and select the cell or cell combination with the best downlink perception rate among these cells according to the estimated downlink perception rate for switching, SN addition, SN change, CA auxiliary carrier addition, CA auxiliary carrier replacement, PSCell change in MR-DC, etc.
  • a rate prediction system for running the rate prediction method is also provided.
  • the rate prediction system as shown in FIG5, an information collection module, a perception rate estimation module and a perception rate application module are set.
  • the information collection module can be used to collect the information required for the neighboring area rate estimation: such as for collecting the cell-level information required for the neighboring area rate estimation; for collecting the UE-level information required for the neighboring area rate estimation.
  • the cell-level information may include at least one of the number of neighboring area users, the neighboring area downlink RB utilization rate, the neighboring area downlink bandwidth and the neighboring area downlink SE grid
  • the UE-level information may include at least one of the neighboring area downlink reference signal RSRP measured by the terminal, the neighboring area downlink reference signal SINR measured by the terminal, the downlink path loss of the terminal in the neighboring area, the location information of the terminal and the chip type of the terminal.
  • the perception rate estimation module can be used to process the information collected by the information collection module to estimate the downlink perception rate of the user in the neighboring area.
  • the perception rate application module can be used to make decisions on operations such as switching based on the downlink perception rate of the user in the neighboring area estimated by the perception rate estimation module.
  • the user position can be determined first, and all cells covered by the user position can be determined. Among all the covered cells, the cells other than the service cell where the terminal held by the user is located are regarded as neighboring cells, and the neighboring cell downlink perception rate of the terminal in each neighboring cell is calculated for each neighboring cell. At this time, the neighboring cell downlink perception rate of each neighboring cell can be calculated by logging in to the target user account in the terminal. The optimal one can be selected according to the downlink sensing rate of each neighboring cell to perform corresponding processing operations.
  • each cell will first build its own fingerprint library, and can share its own fingerprint library with other cells to realize the sharing of fingerprint libraries between cells. Then, if the terminal held by the user needs to perform cell switching or other operation processing, the neighboring cell fingerprint library sent by the target neighboring cell in the service cell can be obtained first.
  • the target neighboring cell can be a neighboring cell that is calculating the neighboring cell downlink perception rate, not a specific one or more cells.
  • the neighboring cell fingerprint library may include at least one set of corresponding relationships between user information and downlink spectrum efficiency.
  • the target neighboring cell constructs the neighboring cell fingerprint library, it is grid-divided according to the user information of the historical user account in the target neighboring cell, and the downlink spectrum efficiency corresponding to the user information belonging to the same grid is added to the corresponding grid to generate. That is, the corresponding relationship between user information and downlink spectrum efficiency will be stored in the neighboring cell fingerprint library.
  • the serving cell may send the target user account and the user information of the target user account to the target neighboring cell, and the target neighboring cell may feedback the neighboring cell downlink perceived rate of the target user account in the target neighboring cell to the serving cell based on the neighboring cell fingerprint library stored in the target neighboring cell.
  • the serving cell may send the target user account and the user information of the target user account to the base station, and the base station may feedback the neighboring cell downlink perceived rate of the target user account in the target neighboring cell to the serving cell based on the neighboring cell fingerprint library of the target neighboring cell.
  • the user information includes at least one of the reference signal received power of the neighboring cell downlink reference signal of the user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, the signal to interference plus noise ratio of the neighboring cell downlink reference signal, the neighboring cell downlink path loss, the chip type and location information.
  • the user information may also include the reference signal received power of the neighboring cell downlink reference signal of the user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, or the signal to interference plus noise ratio of the neighboring cell downlink reference signal.
  • the user information may also add at least one of the neighboring cell downlink path loss, chip type and location information on the basis of the reference signal received power of the neighboring cell downlink reference signal of the user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, or the signal to interference plus noise ratio of the neighboring cell downlink reference signal.
  • the reference signal received power of the neighboring cell downlink reference signal can be the RSRP of the neighboring cell downlink reference signal, which can be a key parameter representing the strength of the wireless signal in the LTE network, and can also be used to measure the downlink coverage.
  • the reference signal reception quality of the neighboring cell downlink reference signal can be the RSRQ of the neighboring cell downlink reference signal, which can be used to measure the reception quality of the neighboring cell downlink reference signal.
  • the signal to interference plus noise ratio of the neighboring cell downlink reference signal can be the SINR of the neighboring cell downlink reference signal, which can be the ratio of the strength of the received useful signal to the strength of the received interference signal (noise and interference).
  • the neighboring cell downlink path loss can be the path loss of the target neighboring cell downlink.
  • the location information can be the coordinate position of the target user account (i.e., the target user account logged in by the terminal held by the user) relative to the target neighboring cell.
  • the reference signal can be a periodic signal sent by the base station or the mobile phone end, which is used by the receiving end as a reference for receiving data from the service channel.
  • Step S20 determining the neighboring cell downlink perceived rate of the target user account in the target neighboring cell based on the neighboring cell fingerprint library.
  • the neighboring cell downlink perception rate of the target user account in the target neighboring cell can be predicted according to the neighboring cell fingerprint library.
  • corresponding processing is performed according to the neighboring cell downlink perception rate. For example, operations such as switching are performed, or after there are multiple neighboring cell downlink perception rates corresponding to the target neighboring cells, one is selected for corresponding processing.
  • the serving cell triggers the prediction of the downlink perceived rate of the neighboring cells.
  • the downlink perception rate prediction process needs to predict the downlink SE of the neighboring cell and obtain the remaining available RB resources of the neighboring cell.
  • each cell first collects user information of the cell to construct a downlink SE fingerprint library, where the collected information includes the downlink reference signal RSRP measured by the terminal, the downlink reference signal SINR measured by the terminal, downlink path loss, chip type, location information, downlink SE, etc.
  • Each cell divides users with the same characteristics into the same category based on the collected downlink reference signal RSRP measured by the terminal, the downlink reference signal SINR measured by the terminal, downlink path loss, chip type, and location information.
  • Each category is a grid, and the mean, maximum, minimum, variance, and other information of the downlink SE of these users are counted in these grids.
  • each cell can generate a fingerprint library of the downlink SE, and then each cell will exchange the constructed fingerprint library with other cells, so that when other cells switch to this cell in the future, the downlink SE of this cell can be predicted.
  • the neighboring cell fingerprint library sent by the target neighboring cell is obtained, and the neighboring cell downlink perception rate of the target user account in the target neighboring cell is determined based on the neighboring cell fingerprint library. This can avoid the phenomenon that only the quality of the neighboring cell downlink channel can be obtained through SRP, RSRQ, and SINR, and the downlink perception rate cannot be fully reflected, resulting in low accuracy of the prediction of the neighboring cell downlink perception rate.
  • the prediction is directly made through the neighboring cell fingerprint library of the target neighboring cell, and the neighboring cell fingerprint library is grid-divided according to the user information of the historical user account, and the downlink spectrum efficiency corresponding to the user information belonging to the same grid is counted, and the downlink spectrum efficiency is added to the corresponding grid to generate, thereby improving the accuracy of the prediction of the neighboring cell downlink perception rate.
  • the neighboring cell downlink perception rate of the target user account in the target neighboring cell it can be achieved in the subsequent switching process based on the predicted neighboring cell downlink perception rate to ensure that the user is always in a cell with optimal downlink perception.
  • step S20 determines the neighboring area downlink perceived rate of the target user account in the target neighboring area based on the neighboring area fingerprint library, including:
  • Step a screening out the downlink spectrum efficiency matching the user information of the target user account from the neighboring cell fingerprint library, and using the matching downlink spectrum efficiency as the neighboring cell downlink spectrum efficiency;
  • the serving cell can directly use the neighboring cell fingerprint library to predict the neighboring cell downlink spectrum efficiency of the target user account in the user's terminal in the neighboring cell.
  • the neighboring cell downlink spectrum efficiency can indicate the amount of data that can be carried and sent on an RB (Resource Block) in the target neighboring cell.
  • the user information corresponding to the target user account can be determined in the serving cell first. That is, various parameter information of the target user account in the target neighboring cell can be collected in the serving cell.
  • the user information of the target user account includes various parameter information, such as the reference signal receiving power of the neighboring cell downlink reference signal of the target user account in the target neighboring cell, the reference signal receiving quality of the neighboring cell downlink reference signal, or the signal to interference plus noise ratio of the neighboring cell downlink reference signal, and can also include the neighboring cell downlink path loss, chip type and location information, etc.
  • the user information of the target user account is matched with the neighboring cell fingerprint library, so as to screen out the downlink spectrum efficiency that matches the user information of the target user account in the neighboring cell fingerprint library.
  • the RSRP in the user information can be matched with the RSRP in the neighboring cell fingerprint library
  • the RSRQ in the user information can be matched with the RSRQ in the neighboring cell fingerprint library
  • the SINR in the user information can be matched with the SINR in the neighboring cell fingerprint library.
  • the neighboring cell downlink path loss, chip type and location information in the user information can also be matched with the neighboring cell downlink path loss, chip type and location information in the neighboring cell fingerprint library.
  • the downlink spectrum efficiency corresponding to the matching user information in the neighboring cell fingerprint library is used as the downlink spectrum efficiency that matches the user information of the target user account, and the matching downlink spectrum efficiency is used as the neighboring cell downlink spectrum efficiency.
  • Step b predicting the neighboring cell downlink perceived rate of the target user account in the target neighboring cell according to the neighboring cell downlink spectrum efficiency.
  • the neighboring area downlink perception rate of the target user account in the target neighboring area can be predicted.
  • the neighboring area downlink perception rate can be the downlink perception rate of the target user account (or the terminal held by the user) in the target neighboring area.
  • the neighboring area downlink perception rate may include the maximum amount of data supported by the target neighboring area per second for scheduling, and the neighboring area downlink spectrum efficiency of the target user account (or the terminal held by the user) in the neighboring area.
  • the serving cell after receiving the measurement report of user switching/multi-carrier addition, obtains the neighboring cell downlink reference signal RSRP and the neighboring cell downlink reference signal SINR from the measurement report, and then locates the grid where the user is located in the neighboring cell downlink SE fingerprint library interacted in the previous period in combination with the downlink path loss of the terminal in the neighboring cell, the chip type of the terminal, and the location information of the terminal, and obtains the downlink SE average of the neighboring cell from the grid, which is used as the neighboring cell downlink SE used for estimating the downlink perception rate of the neighboring cell.
  • RSRP neighboring cell downlink reference signal
  • SINR the neighboring cell downlink reference signal
  • the number of remaining available RBs in the neighboring cell downlink is obtained by combining the actual number of remaining RBs in the neighboring cell (calculated by the number of RBs corresponding to the bandwidth of the neighboring cell and the downlink RB utilization rate of the neighboring cell) and the average number of available RBs per user in the neighboring cell (calculated by the number of RBs corresponding to the bandwidth of the neighboring cell and the number of users in the neighboring cell).
  • the serving cell predicts the downlink perceived rates of different neighboring cells in the measurement report, sorts the neighboring cells from large to small according to the downlink perceived rates, and gives priority to the neighboring cell with the largest perceived rate for switching/multi-carrier addition and other processing.
  • the embodiment of the present application screens out the neighboring cell downlink spectrum efficiency that matches the user information of the target user account in the neighboring cell fingerprint library, and predicts the neighboring cell downlink perception rate of the target user account in the target neighboring cell based on the neighboring cell downlink spectrum efficiency, thereby ensuring the validity of the acquired neighboring cell downlink perception rate.
  • predicting the neighboring cell downlink perceived rate of the target user account in the target neighboring cell according to the neighboring cell downlink spectrum efficiency includes:
  • Step c obtaining the number of available resource blocks remaining in the downlink time slot of the target neighboring cell, and determining the maximum amount of data to be sent in the downlink time slot of the target neighboring cell according to the downlink spectrum efficiency of the neighboring cell and the number of available resource blocks;
  • the serving cell when predicting the neighboring cell downlink perceived rate of the target user account in the target neighboring cell, it is also necessary to evaluate the number of available resource blocks remaining in each downlink time slot in the target neighboring cell in the serving cell, that is, the number of available resource blocks remaining in the downlink time slot in the target neighboring cell. And the serving cell can first obtain the number of available resource blocks actually remaining in the target neighboring cell, and then estimate the number of available resource blocks remaining in each downlink time slot in the target neighboring cell based on the actual number of available resource blocks remaining. Among them, the number of available resource blocks can be the number of resource blocks that can be normally used by the target user account in the downlink time slot in the target neighboring cell.
  • the amount of data that can be sent in each downlink time slot in the target neighboring cell can be directly calculated and used as the maximum amount of data sent in the downlink time slot in the target neighboring cell.
  • the product of the neighboring cell downlink spectrum efficiency and the number of remaining available resource blocks in each downlink time slot in the target neighboring cell can be calculated to obtain the amount of data that can be sent in each downlink time slot in the target neighboring cell, that is, the maximum amount of data sent in the downlink time slot in the target neighboring cell.
  • Step d predicting the neighboring cell downlink perception rate of the target user account in the target neighboring cell according to the maximum amount of data sent and the number of scheduled downlink time slots corresponding to the target neighboring cell.
  • the target neighboring cell After determining the maximum amount of data sent corresponding to each downlink time slot in the target neighboring cell, it is also necessary to obtain the number of downlink time slots that can be used for scheduling in the target neighboring cell within 1 second, and use it as the number of downlink time slots for scheduling, and then calculate the maximum amount of data supported by the neighboring cell per second based on the number of downlink time slots for scheduling and the maximum amount of data sent that can be sent in each downlink time slot in the target neighboring cell, and use it as the predicted neighboring cell downlink perception rate of the target user account in the target neighboring cell.
  • the number of downlink time slots that can be used for scheduling in the target neighboring cell when obtaining the number of downlink time slots that can be used for scheduling in the target neighboring cell within 1 second, it may not be limited to 1 second, but may also be other times, which are not restricted here. And when calculating the neighboring cell downlink perception rate, the maximum amount of data sent corresponding to the number of downlink time slots for scheduling can be added to obtain the neighboring cell downlink perception rate of the target user account in the target neighboring cell.
  • the maximum amount of data to be sent is determined based on the number of available resource blocks remaining in the downlink time slot in the target neighboring cell and the downlink spectrum efficiency of the neighboring cell, and then the neighboring cell downlink perception rate of the target user account in the target neighboring cell is predicted based on the maximum amount of data to be sent and the number of scheduled downlink time slots corresponding to the target neighboring cell, thereby ensuring the accuracy of the predicted neighboring cell downlink perception rate.
  • obtaining the number of available resource blocks remaining in the downlink time slot in the target neighboring cell includes:
  • Step e determining the number of remaining resource blocks in the target neighboring area and the average number of first resource blocks per user account in the target neighboring area;
  • the number of remaining resource blocks of the target neighboring cell may be obtained in the serving cell, and the first number of resource blocks per user account in the target neighboring cell may also be obtained.
  • the number of remaining resource blocks may be the number of resource blocks that can actually be used normally in the target neighboring cell.
  • the first number of resource blocks may be the number of resource blocks that can be used by each user in the target neighboring cell on average.
  • Step f selecting the one with the highest data between the remaining number of resource blocks and the first number of resource blocks as the remaining number of available resource blocks in the downlink time slot in the target neighboring cell.
  • the number of remaining resource blocks and the first number of resource blocks can be compared, and the one with the highest data can be determined according to the comparison result, so as to determine the number of available resource blocks remaining in each downlink time slot in the target neighboring area. For example, if the number of remaining resource blocks in the target neighboring area is greater than the average number of first resource blocks per user account in the target neighboring area, the number of remaining resource blocks can be directly used as the number of available resource blocks remaining in the downlink time slot in the target neighboring area. If the number of first resource blocks is greater than the number of remaining resource blocks in the target neighboring area, the number of first resource blocks can be directly used as the number of available resource blocks remaining in the downlink time slot in the target neighboring area.
  • the validity of the obtained number of available resource blocks is ensured by selecting the highest one between the number of remaining resource blocks in the target neighboring cell and the average number of first resource blocks per user account in the target neighboring cell as the number of available resource blocks remaining in the downlink time slot in the target neighboring cell.
  • determining the number of remaining resource blocks of the target neighboring area and the average number of first resource blocks per user account in the target neighboring area includes:
  • Step g determining the number of second resource blocks corresponding to the bandwidth of the target neighboring cell
  • the target neighboring cell when determining the number of remaining resource blocks of the target neighboring cell, the target neighboring cell may be first obtained in the serving cell.
  • the bandwidth of the target neighboring area is determined, and the number of resource blocks corresponding to the bandwidth is determined, and the number of resource blocks is used as the second number of resource blocks.
  • the corresponding relationship between the bandwidth and the number of resource blocks is set in advance in the protocol, such as 20M bandwidth corresponds to 100 resource blocks. Therefore, the second number of resource blocks corresponding to the bandwidth of the target neighboring area can be directly determined based on the corresponding relationship.
  • Step h determining the number of remaining resource blocks of the target neighboring cell based on the second number of resource blocks and the downlink resource block utilization rate corresponding to the target neighboring cell.
  • the remaining number of resource blocks of the target neighboring area can be calculated according to a preset formula.
  • Step j determining the average number of first resource blocks per user account in the target neighboring area according to the second number of resource blocks and the number of neighboring area user accounts in the target neighboring area.
  • the bandwidth of the target neighboring cell when determining the number of remaining resource blocks of the target neighboring cell, the bandwidth of the target neighboring cell may be first obtained in the serving cell, and the number of resource blocks corresponding to the bandwidth may be determined, and used as the second number of resource blocks.
  • the corresponding relationship between the bandwidth and the number of resource blocks is pre-set in the protocol. Therefore, the second number of resource blocks corresponding to the bandwidth of the target neighboring cell may be directly determined based on the corresponding relationship.
  • the second number of resource blocks is divided by the number of neighboring user accounts to determine or obtain the average number of first resource blocks per user account in the target neighboring area.
  • the remaining number of resource blocks in the target neighboring cell is determined based on the second number of resource blocks corresponding to the bandwidth of the target neighboring cell and the downlink resource block utilization rate, thereby ensuring the accuracy of the determined remaining number of resource blocks, and the average number of first resource blocks per user account in the target neighboring cell is calculated based on the second number of resource blocks corresponding to the bandwidth of the target neighboring cell and the number of neighboring cell user accounts, thereby ensuring the accuracy and effectiveness of the calculated first number of resource blocks.
  • predicting the neighboring cell downlink perceived rate of the target user account in the target neighboring cell according to the neighboring cell downlink spectrum efficiency includes:
  • Step k after there are multiple target neighboring cells, determine the neighboring cell downlink perception rate of the target user account in each target neighboring cell; determine the neighboring cell downlink perception rate with the largest rate among the neighboring cell downlink perception rates, and select the target neighboring cell corresponding to the neighboring cell downlink perception rate with the largest rate for processing.
  • the same processing operation can be performed on each target neighboring cell to obtain the neighboring cell downlink perception rate of the target user account in each target neighboring cell, and then the downlink perception rates of each neighboring cell are processed, and the neighboring cell downlink perception rate with the largest rate is selected, and the target neighboring cell corresponding to the neighboring cell downlink perception rate with the largest rate is used as the target neighboring cell that the target user account finally needs to process.
  • the processing can be cell switching, SN addition, SN change, CA auxiliary carrier addition, CA auxiliary carrier replacement, PSCell in MR-DC, etc. Change processing, etc.
  • the neighboring cell downlink perception rate with the highest rate is determined among the neighboring cell downlink perception rates corresponding to each target neighboring cell, and the target neighboring cell corresponding to the neighboring cell downlink perception rate with the highest rate is selected for processing, thereby ensuring that the user is always in a cell with the best downlink perception.
  • the rate prediction method is applied to a target neighboring area, including:
  • Step S1 dividing the grid according to the user information of the historical user account to obtain multiple grids
  • Step S2 counting the downlink spectrum efficiency corresponding to the user information belonging to the same grid, and adding the downlink spectrum efficiency to the grid to generate a neighboring cell fingerprint library;
  • Step S3 sending the neighboring cell fingerprint library to the serving cell, and the serving cell determines the neighboring cell downlink perceived rate of the target user account in the target neighboring cell based on the neighboring cell fingerprint library.
  • a neighboring cell fingerprint library of the target neighboring cell may be constructed in the target neighboring cell, and after the neighboring cell fingerprint library is constructed, the neighboring cell fingerprint library may be sent to other cells or stored in a storage area of the target neighboring cell.
  • each cell may obtain its own neighboring cell fingerprint library in the same manner as the target neighboring cell.
  • the rate prediction method can be applied to the target neighborhood, and in the target neighborhood, user information of historical user accounts in the target neighborhood is first determined and obtained.
  • the user information of the historical user account may include at least one of the reference signal received power of the neighboring cell downlink reference signal of the historical user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, the signal to interference plus noise ratio of the neighboring cell downlink reference signal, the neighboring cell downlink path loss, the chip type and location information, and may also include the downlink SE, that is, the neighboring cell downlink perceived rate of the historical user account in the target neighboring cell.
  • the collected downlink reference signal RSRP measured by the terminal the downlink reference signal SINR measured by the terminal, the downlink path loss, the chip type, and the location information are divided into the same category for users with the same characteristics.
  • Each category is a grid, and the mean, maximum, minimum, variance and other information of the downlink SE of these users are counted in these grids.
  • the downlink spectrum efficiency corresponding to the historical user information belonging to the same grid can be counted, and the downlink spectrum efficiency can be added to the grid, and after the addition is completed in each grid, it is used as the neighboring cell fingerprint library corresponding to the target neighboring cell.
  • the neighboring cell fingerprint library corresponding to the target neighboring cell.
  • the target neighboring cell after the target neighboring cell generates a neighboring cell fingerprint library, if it is necessary to predict the neighboring cell downlink perception rate of the target user account in the target neighboring cell in the serving cell, the neighboring cell fingerprint library needs to be sent to the serving cell.
  • the serving cell performs the steps of determining the neighboring cell downlink spectrum efficiency corresponding to the target user account in the neighboring cell fingerprint library corresponding to the target neighboring cell; obtaining the number of available resource blocks remaining in the downlink time slot of the target neighboring cell; determining the maximum amount of data sent in the downlink time slot of the target neighboring cell based on the neighboring cell downlink spectrum efficiency and the number of available resource blocks; predicting the neighboring cell downlink perception rate of the target user account in the target neighboring cell based on the maximum amount of data sent and the number of scheduled downlink time slots corresponding to the target neighboring cell, etc.
  • the target neighboring cell can calculate the historical user information in its own cell (such as RSRP of downlink reference signal, downlink).
  • the target neighboring area then counts the downlink SE information corresponding to the historical user information belonging to the same grid in each divided grid, and the target neighboring area generates a neighboring area downlink SE fingerprint library based on the grid results divided by itself and the downlink SE statistics results of the neighboring area users, and uses it as the neighboring area fingerprint library.
  • the library then sends the neighboring area fingerprint library to other cells, such as the service cell where the terminal held by the user is located.
  • the service cell can then directly infer the grid where the user is located in the target neighboring area fingerprint library based on the relevant information of the target user account logged in by the user's terminal, and then determine the neighboring area downlink perception rate of the target user account in the target neighboring area from the corresponding grid.
  • grid division is performed according to user information of historical user accounts, and the downlink spectrum efficiency corresponding to the user information belonging to the same grid is counted and added to the grid to generate a neighboring cell fingerprint library, and then the neighboring cell fingerprint library is sent to the serving cell, so that the serving cell predicts the neighboring cell downlink perception rate of the target user account in the target neighboring cell, thereby avoiding the phenomenon that only the quality of the neighboring cell downlink channel can be obtained through RSRP, RSRQ, and SINR, and the downlink perception rate cannot be fully reflected, resulting in low accuracy of the prediction of the neighboring cell downlink perception rate.
  • the prediction is directly made through the neighboring cell fingerprint library of the target neighboring cell, which improves the accuracy of the prediction of the neighboring cell downlink perception rate. And after the neighboring cell downlink perception rate of the target user account in the target neighboring cell is predicted, switching based on the predicted neighboring cell downlink perception rate can be achieved in the subsequent switching process to ensure that the user is always in a cell with optimal downlink perception.
  • step S2 after adding the downlink spectrum efficiency to the grid and generating a neighboring cell fingerprint library corresponding to the target neighboring cell, includes:
  • Step y receiving the target user account sent by the serving cell and the target user information corresponding to the target user account, determining the neighboring area downlink perception rate of the target user account in the target neighboring area based on the neighboring area fingerprint library, and feeding back the neighboring area downlink perception rate to the serving cell.
  • the target user information includes at least one of the reference signal receiving power of the neighboring cell downlink reference signal of the target user account in the target neighboring cell, the reference signal receiving quality of the neighboring cell downlink reference signal, the signal to interference plus noise ratio of the neighboring cell downlink reference signal, the neighboring cell downlink path loss, the chip type and location information.
  • the target neighboring cell After the target neighboring cell generates a neighboring cell fingerprint library, if it is necessary to predict the neighboring cell downlink perception rate of the target user account in the target neighboring cell. And the target user account and the target user information corresponding to the target user account sent by the serving cell are received in the target neighboring cell, and the neighboring cell downlink spectrum efficiency corresponding to the target user account in the neighboring cell fingerprint library corresponding to the target neighboring cell is determined in the target neighboring cell; the number of available resource blocks remaining in the downlink time slot in the target neighboring cell is obtained; the maximum amount of data sent in the downlink time slot in the target neighboring cell is determined according to the neighboring cell downlink spectrum efficiency and the number of available resource blocks; the neighboring cell downlink perception rate of the target user account in the target neighboring cell is predicted according to the maximum amount of data sent and the number of scheduled downlink time slots corresponding to the target neighboring cell, etc. After determining the neighboring cell downlink perception rate of the target user account in the target neighboring cell, it will also
  • the validity of the predicted neighboring cell downlink perception rate can be guaranteed.
  • a fourth embodiment of the rate prediction method of the present application is proposed.
  • the rate prediction method is applied to a base station, including:
  • Step S100 dividing the grid according to the user information of the historical user account to obtain multiple grids
  • Step S200 counting downlink spectrum efficiencies corresponding to user information belonging to the same grid, and adding the downlink spectrum efficiencies to the grid to generate a neighboring cell fingerprint library;
  • Step S300 determining a neighboring cell downlink perceived rate of a target user account in the target neighboring cell based on the neighboring cell fingerprint library.
  • the base station side can create a fingerprint library corresponding to each cell, that is, a neighboring cell fingerprint library.
  • the neighboring cell fingerprint library can be exchanged between the cells, that is, each cell can store and retain the neighboring cell fingerprint library of the adjacent cell.
  • the way to construct the neighboring fingerprint library of each cell is the same, and grid division can be performed according to the user information of the historical user accounts in the cell to obtain multiple grids.
  • the collected downlink reference signal RSRP measured by the terminal, the downlink reference signal SINR measured by the terminal, the downlink path loss, the chip type, and the location information are divided into the same category for users with the same characteristics.
  • Each category is a grid, and the mean, maximum, minimum, variance and other information of the downlink SE of these users are counted in these grids.
  • the downlink spectrum efficiency corresponding to the historical user information belonging to the same grid can be counted, and this downlink spectrum efficiency can be added to the grid, and after it is added to each grid, it is used as a neighboring fingerprint library. So that the neighboring downlink perception rate of the target user account in the target neighboring area can be directly determined in the service cell or the target neighboring area according to the neighboring fingerprint library.
  • the user information of the historical user account includes at least one of the reference signal received power of the neighboring cell downlink reference signal of the historical user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, the signal to interference plus noise ratio of the neighboring cell downlink reference signal, the neighboring cell downlink path loss, the chip type and location information.
  • the user information of the historical user account includes the reference signal received power of the neighboring cell downlink reference signal of the historical user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, or the signal to interference plus noise ratio of the neighboring cell downlink reference signal.
  • the user information of the historical user account can also be based on the reference signal received power of the neighboring cell downlink reference signal of the historical user account in the target neighboring cell, the reference signal received quality of the neighboring cell downlink reference signal, or the signal to interference plus noise ratio of the neighboring cell downlink reference signal, and at least one of the neighboring cell downlink path loss, chip type and location information.
  • the base station After the base station determines the neighboring cell fingerprint library in the target neighboring cell, it can directly obtain the user information of the target user account, and filter out the downlink spectrum efficiency matching the user information of the target user account in the neighboring cell fingerprint library, and then send it to the serving cell.
  • the neighboring cell fingerprint library can be sent to the serving cell, and the serving cell determines the neighboring cell downlink perception rate of the target user account in the target neighboring cell based on the neighboring cell fingerprint library.
  • the serving cell can select the downlink spectrum efficiency that matches the user information of the target user account from the neighboring cell fingerprint library, that is, the neighboring cell downlink spectrum efficiency, and then obtain the number of available resource blocks remaining in the downlink time slot in the target neighboring cell, predict the maximum amount of data sent in the downlink time slot in the target neighboring cell based on the number of available resource blocks and the neighboring cell downlink spectrum efficiency, and then predict the neighboring cell downlink perception rate of the target user account in the target neighboring cell based on the maximum amount of data sent and the number of scheduled downlink time slots corresponding to the target neighboring cell.
  • the base station may detect the target user account and target user account sent by the serving cell. After obtaining the user information of the target user account, the target user account and the user information of the target user account are sent to the target neighboring cell, so that the target neighboring cell can determine the neighboring cell downlink perception rate of the target user account in the target neighboring cell according to its own neighboring cell fingerprint library and the user information of the target user account, and feed back the neighboring cell downlink perception rate to the base station, which is then fed back to the serving cell.
  • the grid is divided according to the user information of the historical user account, and the downlink spectrum efficiency corresponding to the user information belonging to the same grid is counted and added to the grid to generate a neighboring cell fingerprint library, and then the neighboring cell downlink perception rate of the target user account in the target neighboring cell is determined according to the neighboring cell fingerprint library, thereby avoiding the phenomenon that only the quality of the neighboring cell downlink channel can be obtained through RSRP, RSRQ, and SINR, and the downlink perception rate cannot be fully reflected, resulting in low accuracy of the prediction of the neighboring cell downlink perception rate.
  • the prediction is made directly through the neighboring cell fingerprint library of the target neighboring cell, which improves the accuracy of the prediction of the neighboring cell downlink perception rate.
  • switching based on the predicted neighboring cell downlink perception rate can be achieved in the subsequent switching process to ensure that the user is always in a cell with optimal downlink perception.
  • the present application also provides an electronic device, which includes a memory, a processor, and a rate prediction program stored in the memory and executable on the processor.
  • a rate prediction program stored in the memory and executable on the processor.
  • FIG6 is a schematic diagram of the structure of an electronic device of an embodiment of the present application.
  • the electronic device includes a processor, and optionally also includes an internal bus, a network interface, and a memory.
  • the memory may include a memory, such as a high-speed random access memory (Random-Access Memory, RAM), and may also include a non-volatile memory (non-volatile memory), such as at least one disk storage, etc.
  • RAM random access memory
  • non-volatile memory non-volatile memory
  • the electronic device may also include hardware required for other services.
  • the processor, the network interface, and the memory may be interconnected through an internal bus, and the internal bus may be an ISA (Industry Standard Architecture) bus, a PCI (Peripheral Component Interconnect) bus, or an EISA (Extended Industry Standard Architecture) bus, etc.
  • the bus can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, only one bidirectional arrow is used in FIG6, but it does not mean that there is only one bus or one type of bus.
  • the memory is used to store programs.
  • the program may include a program code, and the program code includes a computer operation instruction.
  • the processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it, forming a shared resource access control device at the logical level.
  • the processor executes the program stored in the memory and is specifically used to execute the steps of the above-mentioned rate prediction method.
  • the present application also provides a computer-readable storage medium, on which a rate prediction program is stored.
  • a rate prediction program is stored on which a rate prediction program is stored.
  • all or some steps, systems, and functional modules/units in the above disclosed methods can be implemented as software, firmware, hardware, and appropriate combinations thereof.
  • the division between the functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component can have multiple functions, or a function or step can be performed by several physical components in cooperation.
  • the physical components or all physical components can be implemented as software executed by a processor, such as a central processing unit, a digital signal processor or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit.
  • Such software can be distributed on a computer-readable medium
  • the computer-readable medium may include a computer storage medium (or a non-temporary medium) and a communication medium (or a temporary medium).
  • the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data).
  • Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disk (DVD) or other optical disk storage, magnetic cassette, magnetic tape, disk storage or other magnetic storage device, or any other medium that can be used to store desired information and can be accessed by a computer.
  • communication media generally contain computer-readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transmission mechanism, and may include any information delivery medium.

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Abstract

本申请公开了一种速率预测方法、电子设备及计算机可读存储介质，速率预测方法包括：获取目标邻区发送的邻区指纹库，其中，所述邻区指纹库是根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将所述下行频谱效率添加至对应栅格内生成的；基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。

Description

速率预测方法、电子设备及计算机可读存储介质
相关申请
本申请要求于2023年2月20号申请的、申请号为202310183548.3的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信技术领域，尤其涉及一种速率预测方法、电子设备及计算机可读存储介质。
背景技术
目前是基于RSRP(Reference Signal Receiving Power，参考信号接收功率)、RSRQ(Reference Signal Receiving Quality，参考信号接收质量)和SINR(Signal to Interference plus Noise Ratio，信号与干扰加噪声比)来评估用户是否需要触发切换邻区，但是RSRP、RSRQ、SINR只能反应下行信道的质量情况，无法完全反应用户的下行感知体验。而在实际生活当中手机的使用者更关心的是下行感知速率，而下行信道质量仅仅是影响下行感知速率的其中一个因素，不能完全反应下行感知速率情况。因此，使用传统的邻区评估方式得到的结果会与用户实际希望的结果产生偏差，无法满足用户的预期。
发明内容
本申请的主要目的在于提供一种速率预测方法、电子设备及计算机可续存储介质，旨在解决如何提高邻区下行感知速率预测的准确性的技术问题。
为实现上述目的，本申请提供了一种速率预测方法，应用于服务小区，包括：
获取目标邻区发送的邻区指纹库，其中，所述邻区指纹库是根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将所述下行频谱效率添加至对应栅格内生成的；
基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。
此外，为实现上述目的，本申请还提供了一种速率预测方法，应用于目标邻区，包括：
根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加至所述栅格内，生成邻区指纹库；
将所述邻区指纹库发送至服务小区，所述服务小区基于所述邻区指纹库确定所述目标用户账号在所述目标邻区的邻区下行感知速率。
此外，为实现上述目的，本申请还提供了一种速率预测方法，应用于基站，包括：
根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加 至所述栅格内，生成邻区指纹库；
基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。
此外，为实现上述目的，本申请还提供了一种电子设备，上述电子设备包括：存储器、处理器及存储在上述存储器上并可在上述处理器上运行的速率预测程序，上述速率预测程序被上述处理器执行时实现如上述的速率预测方法的步骤。
此外，为实现上述目的，本申请还提供了一种计算机可读存储介质，上述计算机可读存储介质上存储有速率预测程序，上述速率预测程序被处理器执行时实现如上述的速率预测方法的步骤。
附图说明
图1为本申请速率预测方法第一实施例的流程示意图；
图2为本申请速率预测方法第二实施例的流程示意图；
图3为本申请速率预测方法第三实施例的流程示意图；
图4为本申请速率预测方法第四实施例的流程示意图；
图5为本申请速率预测方法中速率预测系统的模块示意图；
图6为本申请实施例中速率预测方法涉及的硬件运行环境的设备结构示意图。
本申请目的实现、功能特点及优点将结合实施例，参照附图做进一步说明。
具体实施方式
应当理解，此处所描述的具体实施例仅仅用以解释本申请，并不用于限定本申请。
在无线通信系统中，伴随着用户移动位置的变化，网络侧要实时监控用户的服务质量，保证用户的感知体验最优。
通常情况下，基站通过监测终端在服务小区和邻区的RSRP(Reference Signal Receiving Power，参考信号接收功率)、RSRQ(Reference Signal Receiving Quality，参考信号接收质量)、SINR(Signal to Interference plus Noise Ratio，信号与干扰加噪声比)值来评估用户是否需要触发切换。当存在多个候选切换邻区时，也是基于RSRP、RSRQ、SINR对邻区进行选择。而RSRP、RSRQ、SINR只能反应下行信道的质量情况，无法完全反应用户的下行感知体验，从而导致邻区下行感知速率预测的准确性较低。因此在本实施例中为避免这一缺陷，是提前预测出用户在邻区的下行感知速率，这样在切换过程中就可以基于感知速率对邻区进行选择，确保用户时刻都处于一个下行感知最优的小区。比如对于下载类的用户，对下行速率的需求较大，此时就可以基于下行感知速率为用户选择下行感知速率最大的邻区。而且在进行下行感知速率预测的过程中，首先需要预测出用户在邻区的下行频谱效率(SE，spectral efficiency)，可以使用邻区的平均下行SE。但是，邻区平均下行SE只能反应邻区的平均水平，并不能代表特定用户的真实情况，因此使用邻区平均下行SE进行速率预测会存在很大的误差。因此在本实施例中，可以是借助邻区指纹库来进行邻区下行SE预测，以提高邻区下行感知速率预测的准确性。
并且在本实施例中，可以评估用户在邻区的下行感知速率，可以应用在通信系统中，在通信系统的移动性过程中(如切换、PSCell(Primary Secondary Cell，主辅小区)变更、SN(Secondary Node，辅节点)添加/变更、CA(Carrier Aggregatio、载波聚合)辅载波添加/变更)，对用户在邻区的下行感知速率进行预估，为用户选择一个下行感知速率最佳的小区。还可以通过一些与SE强相关的指标和历史用户的调度SE关联，构建SE栅格。在切换前从邻区获取这些与SE强相关的指标取值，然后查询SE栅格，即可得到邻区的SE信息。
下面结合附图，对本申请实施例做进一步阐述。
参照图1，本申请提供一种速率预测方法，在速率预测方法的第一实施例中，速率预测方法，应用于服务小区，包括：
步骤S10，获取目标邻区发送的邻区指纹库，所述邻区指纹库是根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将所述下行频谱效率添加至对应栅格内生成的；
在移动通信系统中，随着用户的移动，用户所使用的终端可能从当前服务小区的覆盖范围移动到另一个小区的覆盖范围。当UE服务小区的无线信号质量较差时，通常需要将UE切换到无线信号质量更好的邻近小区(即邻区)，这个过程称为切换。
在本实施例中，当用户处于多小区覆盖区域内时，需要给用户选择一个下行感知速率最好小区进行切换、SN添加、SN变更、CA辅载波添加、CA辅载波替换、MR-DC(Multi-Rate Dual Connectivity，多系统双连接)中PSCell变更等处理时，可以通过本实施例中的方式来预估用户所持终端对应的目标用户账号在不同小区的下行感知速率，并根据预估的下行感知速率在这些小区中挑选下行感知速率最好的小区或小区组合进行切换、SN添加、SN变更、CA辅载波添加、CA辅载波替换、MR-DC中PSCell变更等处理。
并且在本实施例中，还会提供一种用于运行速率预测方法的速率预测系统，在速率预测系统中，会如图5所示，设置信息采集模块，感知速率预估模块和感知速率应用模块。并且信息采集模块可以用于对邻区速率预估所需的信息进行收集：如用于收集邻区速率预估所需的小区级信息；用于收集邻区速率预估所需的UE级信息。其中，小区级信息可以包括邻区用户数、邻区下行RB利用率、邻区下行带宽和邻区下行SE栅格中的至少一种，UE级信息可以包括终端测量的邻区下行参考信号RSRP、终端测量的邻区下行参考信号SINR、终端在邻区的下行路损、终端的位置信息和终端的芯片类型中的至少一种。感知速率预估模块可以用于将信息采集模块收集的信息进行处理，预估出用户在邻区的下行感知速率。感知速率应用模块可以用于根据感知速率预估模块预估的用户在邻区的下行感知速率进行切换等操作的判决。
因此，在本实施例中，当用户所持终端在服务小区中需要进行切换、SN添加、SN变更、CA辅载波添加、CA辅载波替换、MR-DC中PSCell变更等处理时，可以先确定用户位置，并确定该用户位置上覆盖的所有小区，将覆盖的所有小区中除用户所持终端所在的服务小区之外的其他小区作为邻区，并对每个邻区进行计算终端在各个邻区的邻区下行感知速率，此时可以通过登录在终端中的目标用户账号在各个邻区的邻区下行感知速率进行 确定。并可以根据各个邻区下行感知速率选择最优的一个进行相应的处理操作。
因此在本实施例中，各个小区会先构建好各自的指纹库，并可以将各自的指纹库分享至其他小区，以实现小区之间的指纹库共享。然后若用户所持终端需要进行小区切换或其他操作处理时，可以先获取服务小区中目标邻区发送的邻区指纹库。其中，目标邻区可以是正在进行计算邻区下行感知速率的邻区，并不是特指的某一个或多个小区。邻区指纹库可以包括至少一组用户信息与下行频谱效率之间的对应关系。并且目标邻区在构建邻区指纹库时，是根据目标邻区中历史用户账号的用户信息进行栅格划分，并将隶属于同一栅格内的用户信息对应的下行频谱效率添加至对应栅格内生成的。也就是邻区指纹库中会存储有用户信息与下行频谱效率之间的对应关系。
此外，在一场景中，还可以是服务小区将目标用户账号和目标用户账号的用户信息发送至目标邻区，目标邻区根据自身存储的邻区指纹库反馈目标用户账号在目标邻区的邻区下行感知速率至服务小区。还可以是服务小区将目标用户账号和目标用户账号的用户信息发送至基站，基站根据目标邻区的邻区指纹库反馈目标用户账号在目标邻区的邻区下行感知速率至服务小区。
用户信息包括用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。
在一实施方式中，用户信息还可以包括用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量或者邻区下行参考信号的信号与干扰加噪声比。另外为辅助提高邻区指纹库中栅格划分的准确性，用户信息还可以在用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量或者邻区下行参考信号的信号与干扰加噪声比的基础上，增加邻区下行路损、芯片类型和位置信息等中的至少一种。
其中，邻区下行参考信号的参考信号接收功率可以是邻区下行参考信号的RSRP，可以是LTE网络中代表无线信号强度的关键参数，也可以用于衡量下行的覆盖。邻区下行参考信号的参考信号接收质量可以是邻区下行参考信号的RSRQ，可以用于衡量邻区下行参考信号的接收质量。邻区下行参考信号的信号与干扰加噪声比可以是邻区下行参考信号的SINR，可以是接收到的有用信号的强度与接收到的干扰信号(噪声和干扰)的强度的比值。邻区下行路损可以是目标邻区下行的路径损耗。位置信息可以是目标用户账号(即用户所持终端登录的目标用户账号)相对于目标邻区的坐标位置。参考信号可以是基站或手机端发出的周期性信号，用于接收端作为从业务信道接收数据的参考。
步骤S20，基于所述邻区指纹库确定目标用户账号在目标邻区的邻区下行感知速率。
在本实施例中，在服务小区获取或确定至少一个目标邻区发送的邻区指纹库之后，就可以根据邻区指纹库来预测目标用户账号在目标邻区的邻区下行感知速率。并根据邻区下行感知速率进行相应处理。如进行切换等操作，或者是在存在多个目标邻区对应的邻区下行感知速率之后，从中选择一个进行相应的处理。
例如，对于触发切换/多载波添加等过程的用户在测量报告中上报多个邻区，且需要给用户选择一个下行感知速率最佳的小区时，服务小区触发对邻区的下行感知速率预测。 其中，下行感知速率预测过程需要预测邻区的下行SE以及获取邻区剩余可用的RB资源。
例如，每个小区先各自收集本小区的用户信息进行下行SE指纹库的构建，其中收集的信息包含终端测量的下行参考信号RSRP、终端测量的下行参考信号SINR、下行路损、芯片类型、位置信息、下行SE等。每个小区基于收集的终端测量的下行参考信号RSRP、终端测量的下行参考信号SINR、下行路损、芯片类型、位置信息将具有相同特征的用户划分到相同的类别中，每一个类别就是一个栅格，在这些栅格中统计这些用户的下行SE的均值、最大值、最小值、方差等信息。通过以上方式每个小区可以生成下行SE的指纹库，然后每个小区将构建好的指纹库交互给其他小区，便于后续其他小区向本小区切换时，预测本小区的下行SE。
在本实施例中，通过获取目标邻区发送的邻区指纹库，并基于邻区指纹库确定目标用户账号在目标邻区的邻区下行感知速率。从而可以避免通过SRP、RSRQ、SINR只能获取到邻区下行信道的质量情况，不能完全反应下行感知速率，导致邻区下行感知速率预测的准确性低的现象发生，并且是直接通过目标邻区的邻区指纹库进行预测的，而邻区指纹库是根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将下行频谱效率添加至对应栅格生成的，因此也提高了邻区下行感知速率预测的准确性。并且在预测得到目标用户账号在目标邻区的邻区下行感知速率后，可以实现在后续进行切换过程中基于预测的邻区下行感知速率进行切换，以确保用户时刻都处于一个下行感知最优的小区。
基于上述本申请的第一实施例，提出本申请速率预测方法的第二实施例，在本实施例中，参照图2，上述步骤S20，基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率，包括：
步骤a，在所述邻区指纹库中筛选出与目标用户账号的用户信息匹配的下行频谱效率，并将匹配的所述下行频谱效率作为邻区下行频谱效率；
在本实施例中，服务小区可以直接借助邻区指纹库预测用户所持终端中目标用户账号在邻区的邻区下行频谱效率。邻区下行频谱效率可以表示目标邻区中一个RB(Resource Block，资源块)上可以承载发送的数据量。
在预测邻区下行频谱效率时，可以是先在服务小区中确定目标用户账号对应的用户信息。也就是可以在服务小区中采集目标用户账号在目标邻区中的各类参数信息。目标用户账号的用户信息包括各类参数信息，如目标用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量或者邻区下行参考信号的信号与干扰加噪声比，还可以包括邻区下行路损、芯片类型和位置信息等。
然后将目标用户账号的用户信息与邻区指纹库进行匹配，以便在邻区指纹库中筛选出与目标用户账号的用户信息匹配的下行频谱效率。在进行匹配时，可以是将用户信息中的RSRP与邻区指纹库中的RSRP进行匹配、将用户信息中的RSRQ与邻区指纹库中的RSRQ进行匹配，或者是将用户信息中的SINR与邻区指纹库中的SINR进行匹配等。此外还可以将用户信息中的邻区下行路损、芯片类型和位置信息与邻区指纹库中的邻区下行路损、芯片类型和位置信息进行匹配。
并在邻区指纹库中确定与目标用户账号的用户信息匹配的用户信息之后，将邻区指纹库中与匹配的用户信息对应的下行频谱效率作为与目标用户账号的用户信息匹配的下行频谱效率，并将匹配的下行频谱效率作为邻区下行频谱效率。
步骤b，根据所述邻区下行频谱效率预测所述目标用户账号在目标邻区的邻区下行感知速率。
在通过邻区指纹库获取到目标用户账号在目标邻区的邻区下行频谱效率之后，就可以进行目标用户账号在目标邻区的邻区下行感知速率的预测。其中，邻区下行感知速率可以是目标用户账号(也可以是用户所持终端)在目标邻区的下行感知速率。所述邻区下行感知速率可以包括目标邻区每秒支持调度的最大数据量，以及目标用户账号(也可以是用户所持终端)在邻区的邻区下行频谱效率。
例如，服务小区收到用户切换/多载波添加等的测量报告后，从测量报告中获取邻区下行参考信号RSRP、邻区下行参考信号SINR，再结合终端在邻区的下行路损、终端的芯片类型、终端的位置信息在前期交互的邻区下行SE指纹库中定位用户所处的栅格，并从栅格中查询得到邻区的下行SE均值，作为邻区下行感知速率预估使用的邻区下行SE。基于上述获取的邻区下行SE，再结合从邻区获取的下行剩余可用RB数量，计算得到邻区每个时隙最大支持发送的数据量。其中，邻区下行剩余可用RB数由邻区实际剩余的RB数(由邻区带宽对应RB数和邻区下行RB利用率计算得到)以及邻区平均每用户的可用RB数(由邻区带宽对应RB数和邻区用户数计算得到)综合得到。最后，结合邻区1秒内可用于调度的下行时隙数，计算得到邻区1秒内支持调度的最大数据量，即为预测的邻区下行感知速率。此时，服务小区分别预测出了测量报告中不同邻区的下行感知速率，按照下行感知速率从大到小对邻区进行排序，优先选择感知速率最大的邻区进行切换/多载波添加等处理。
本申请实施例通过在邻区指纹库中筛选出与目标用户账号的用户信息匹配的邻区下行频谱效率，并根据邻区下行频谱效率预测目标用户账号在目标邻区的邻区下行感知速率，从而保障了获取到的邻区下行感知速率的有效性。
在一实施方式中，根据所述邻区下行频谱效率预测所述目标用户账号在目标邻区的邻区下行感知速率，包括：
步骤c，获取所述目标邻区中下行时隙剩余的可用资源块数，根据所述邻区下行频谱效率和所述可用资源块数确定所述目标邻区中下行时隙的最大发送数据量；
在本实施例中，在预测目标用户账号在目标邻区的邻区下行感知速率时，还需要在服务小区评估目标邻区中每个下行时隙剩余可用的资源块数目，也就是目标邻区中下行时隙剩余的可用资源块数。并且服务小区可以先获取目标邻区中实际上剩余可用的资源块数，然后根据实际剩余可用的资源块数来预估获取目标邻区中每个下行时隙剩余的可用资源块数。其中，可用资源块数可以是目标邻区中下行时隙中可以被目标用户账号正常使用的资源块数目。
在根据目标邻区指纹库获取到目标用户账号在目标邻区的邻区下行频谱效率，以及目标邻区中每个下行剩余可用的可用资源块数之后，可以直接计算目标邻区中每个下行时隙可以发送的数据量，并将其作为目标邻区中下行时隙的最大发送数据量。在一实施方式中， 在确定目标邻区中下行时隙的最大发送数据量时，可以计算邻区下行频谱效率和目标邻区中每个下行时隙剩余可用的资源块数目之间的乘积，得到目标邻区中每个下行时隙可以发送的数据量，即目标邻区中下行时隙的最大发送数据量。
步骤d，根据所述最大发送数据量和所述目标邻区对应的调度下行时隙数预测所述目标用户账号在所述目标邻区的邻区下行感知速率。
在确定目标邻区中每个下行时隙对应的最大发送数据量之后，还需要获取目标邻区1秒内可用于调度的下行时隙数，并将其作为调度下行时隙数，然后根据调度下行时隙数和目标邻区中每个下行时隙可以发送的最大发送数据量计算得到邻区每秒支持调度的最大数据量，并将其作为预测的目标用户账号在目标邻区中的邻区下行感知速率。其中，获取目标邻区1秒内可用于调度的下行时隙数时，也可以不局限于1秒，还可以是其他时间，在此不做限制。并且在计算邻区下行感知速率时，可以将调度下行时隙数个下行时隙对应的最大发送数据量进行相加得到目标用户账号在目标邻区的邻区下行感知速率。
在本实施例中，通过根据目标邻区中下行时隙剩余的可用资源块数和邻区下行频谱效率来确定最大发送数据量，再根据最大发送数据量和目标邻区对应的调度下行时隙数预测目标用户账号在目标邻区的邻区下行感知速率，从而保障了预测的邻区下行感知速率的准确性。
在一实施方式中，获取所述目标邻区中下行时隙剩余的可用资源块数，包括：
步骤e，确定所述目标邻区的剩余资源块数和所述目标邻区中平均每用户账号的第一资源块数；
在本实施例中，在确定目标邻区中每个下行时隙剩余的可用资源块数时，可以在服务小区中获取目标邻区的剩余资源块数，还需要获取目标邻区中平均每用户账号的第一资源块数。其中，剩余资源块数可以是目标邻区中实际上可以正常使用的资源块数。第一资源块数可以是目标邻区中每个用户平均可以使用的资源块数。
步骤f，选择所述剩余资源块数和所述第一资源块数中数据最高的一个作为所述目标邻区中下行时隙剩余的可用资源块数。
在获取到剩余资源块数和第一资源块数之后，就可以将剩余资源块数和第一资源块数进行比较，并根据比较结果确定数据最高的一个，以便确定目标邻区中每个下行时隙剩余的可用资源块数。例如目标邻区的剩余资源块数大于目标邻区中平均每用户账号的第一资源块数，则可以直接将剩余资源块数作为目标邻区中下行时隙剩余的可用资源块数。若第一资源块数大于目标邻区的剩余资源块数，则可以直接将第一资源块数作为目标邻区中下行时隙剩余的可用资源块数。
在本实施例中，通过选择目标邻区的剩余资源块数和目标邻区中平均每用户账号的第一资源块数中数据最高的一个作为目标邻区中下行时隙剩余的可用资源块数，从而保障了获取到的可用资源块数的有效性。
在一实施例中，确定所述目标邻区的剩余资源块数和所述目标邻区中平均每用户账号的第一资源块数，包括：
步骤g，确定所述目标邻区的带宽对应的第二资源块数；
在本实施例中，在确定目标邻区的剩余资源块数时，可以先在服务小区中获取目标邻 区的带宽，并确定该带宽对应的资源块数，并将其作为第二资源块数。其中带宽和资源块数之间的对应关系是协议中提前设置好的，如20M带宽对应100个资源块数。因此可以根据对应关系直接确定目标邻区的带宽对应的第二资源块数。
在本实施例中，还需要确定目标邻区对应的下行资源块利用率。其中，下行资源块利用率可以是提前设置好的默认值，也可以是根据实际使用的资源块数进行计算确定的。例如假设存在100个资源块数，若实际用了70个资源块数，则其下行资源块利用率为70/100＝70％。
步骤h，依据所述第二资源块数和所述目标邻区对应的下行资源块利用率确定所述目标邻区的剩余资源块数。
在确定第二资源块数和下行资源块利用率后，可以按照预设的公式进行计算得到目标邻区的剩余资源块数。其中，预设的公式可以是第二资源块数*(1-下行资源块利用率)＝目标邻区的剩余资源块数。例如，若第二资源块数为100，下行资源块利用率为70％，则目标邻区的剩余资源块数可以是100*(1-70％)＝30。
步骤j，依据所述第二资源块数和所述目标邻区中的邻区用户账号数确定所述目标邻区中平均每用户账号的第一资源块数。
在本实施例中，在确定目标邻区的剩余资源块数时，可以先在服务小区中获取目标邻区的带宽，并确定该带宽对应的资源块数，并将其作为第二资源块数。其中带宽和资源块数之间的对应关系是协议中提前设置好的。因此可以根据对应关系直接确定目标邻区的带宽对应的第二资源块数。
在本实施例中，还需要获取目标邻区中可以使用的邻区用户账号的最大账号数，并将其作为邻区用户账号数。然后再将第二资源块数除以邻区用户账号数，以确定或得到目标邻区中平均每用户账号的第一资源块数。
在本实施例中，通过依据目标邻区的带宽对应的第二资源块数，以及下行资源块利用率来确定目标邻区的剩余资源块数，从而保障了确定的剩余资源块数的准确性，并通过依据目标邻区的带宽对应的第二资源块数，以及邻区用户账号数来计算确定目标邻区中平均每用户账号的第一资源块数，从而保障了计算得到的第一资源块数的准确有效性。
在一实施方式中，根据所述邻区下行频谱效率预测目标用户账号在目标邻区的邻区下行感知速率之后，包括：
步骤k，在所述目标邻区存在多个之后，确定所述目标用户账号在每个目标邻区的邻区下行感知速率；确定各所述邻区下行感知速率中速率最大的邻区下行感知速率，并选择速率最大的邻区下行感知速率对应的目标邻区进行处理。
在本实施例中，当在服务小区中，确定用户所持终端中登录的目标用户账号同时处于多个小区的覆盖范围之后，就可以将这些小区中除服务小区之外的其他小区均作为目标邻区。因此在服务小区检测到存在多个目标邻区之后，可以对每个目标邻区进行相同的处理操作，以得到目标用户账号在每个目标邻区中的邻区下行感知速率，然后再对各个邻区下行感知速率进行，并从中选择一个速率最大的邻区下行感知速率，再将此速率最大的邻区下行感知速率对应的目标邻区作为目标用户账号最终需要进行处理的目标邻区。其中，处理可以是小区切换、SN添加、SN变更、CA辅载波添加、CA辅载波替换、MR-DC中PSCell 变更等处理。
在本实施例中，通过在目标邻区存在多个之后，在每个目标邻区对应的邻区下行感知速率中确定速率最大的邻区下行感知速率，并选择该速率最大的邻区下行感知速率对应的目标邻区进行处理，从而保障了用户时刻都处于一个下行感知最优的小区。
基于上述本申请的第一或第二实施例，提出本申请速率预测方法的第三实施例，在本实施例中，参照图3，速率预测方法，应用于目标邻区，包括：
步骤S1，根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
步骤S2，统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加至所述栅格内，生成邻区指纹库；
步骤S3，将所述邻区指纹库发送至服务小区，所述服务小区基于所述邻区指纹库确定所述目标用户账号在所述目标邻区的邻区下行感知速率。
在本实施例中，可以是在目标邻区中构建目标邻区的邻区指纹库，并在构建完成邻区指纹库之后，可以将邻区指纹库发送至其他各个小区，也可以保存在目标邻区的存储区域。并且在本实施例中，各个小区都可以按照和目标邻区相同的方式来获取自身的邻区指纹库。
因此，在本实施例中，速率预测方法可以应用于目标邻区，并且在目标邻区内，先确定并获取目标邻区内历史用户账号的用户信息。
在一实施方式中，历史用户账号的用户信息可以包括历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种，还可以包括下行SE，即历史用户账号在目标邻区的邻区下行感知速率。
并根据历史用户信息进行栅格划分，以得到多个栅格。例如，将收集的终端测量的下行参考信号RSRP、终端测量的下行参考信号SINR、下行路损、芯片类型、位置信息将具有相同特征的用户划分到相同的类别中，每一个类别就是一个栅格，在这些栅格中统计这些用户的下行SE的均值、最大值、最小值、方差等信息。
在一实施方式中，可以在进行栅格划分之后，统计隶属于同一栅格内的历史用户信息对应的下行频谱效率，并将此下行频谱效率添加至栅格内，并在各个栅格内都添加完成之后，就将其作为目标邻区对应的邻区指纹库。以便后续在服务小区或者目标邻区中根据邻区指纹库直接确定目标用户账号在目标邻区的邻区下行感知速率。
在一实施例中，当目标邻区生成邻区指纹库之后，若需要在服务小区中进行目标用户账号在目标邻区的邻区下行感知速率的预测，则需要将邻区指纹库发送至服务小区。然后服务小区再执行确定目标邻区对应的邻区指纹库中与目标用户账号对应的邻区下行频谱效率；获取所述目标邻区中下行时隙剩余的可用资源块数；根据所述邻区下行频谱效率和所述可用资源块数确定所述目标邻区中下行时隙的最大发送数据量；根据所述最大发送数据量和所述目标邻区对应的调度下行时隙数预测所述目标用户账号在所述目标邻区的邻区下行感知速率等步骤。
例如，目标邻区根据自己小区内历史用户的信息(比如下行参考信号的RSRP、下行 参考信号的RSRQ或SINR、用户的位置信息、用户使用终端的芯片类型)，对自己进行栅格划分、其中，划分栅格所需的历史用户信息中，可以根据下行参考信号的RSRP、下行参考信号的RSRQ或SINR。还可以选择用户的位置信息，和/或，芯片类型以辅助提高栅格划分的准确度。然后目标邻区在划分出的各栅格内，将隶属于同一个栅格内的历史用户信息对应的下行SE信息进行统计，目标邻区根据自己划分的栅格结果和邻区用户的下行SE统计结果，生成邻区下行SE指纹库，并将其作为邻区指纹库。然后库将邻区指纹库发送至其他的小区，如用户所持终端所在的服务小区。然后服务小区就可以直接根据用户所持终端登录的目标用户账号的相关信息推测用户在目标邻区指纹库中所处的栅格，然后从对应的栅格中确定目标用户账号在目标邻区的邻区下行感知速率。
在本实施例中，通过根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将其添加至栅格内，以生成邻区指纹库，再将邻区指纹库发送至服务小区，以使服务小区预测目标用户账号在目标邻区的邻区下行感知速率，从而可以避免通过RSRP、RSRQ、SINR只能获取到邻区下行信道的质量情况，不能完全反应下行感知速率，导致邻区下行感知速率预测的准确性低的现象发生，并且是直接通过目标邻区的邻区指纹库进行预测的，提高了邻区下行感知速率预测的准确性。并且在预测得到目标用户账号在目标邻区的邻区下行感知速率后，可以实现在后续进行切换过程中基于预测的邻区下行感知速率进行切换，以确保用户时刻都处于一个下行感知最优的小区。
在一实施例中，步骤S2，将所述下行频谱效率添加至所述栅格内，生成所述目标邻区对应的邻区指纹库之后，包括：
步骤y，接收服务小区发送的目标用户账号以及所述目标用户账号对应的目标用户信息，依据所述邻区指纹库确定所述目标用户账号在所述目标邻区的邻区下行感知速率，将所述邻区下行感知速率反馈至服务小区。
在本实施例中，所述目标用户信息包括所述目标用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。
在本实施例中，当目标邻区生成邻区指纹库之后，若需要在目标邻区中进行目标用户账号在目标邻区的邻区下行感知速率的预测。且在目标邻区中接收到服务小区发送的目标用户账号以及目标用户账号对应的目标用户信息，并会在目标邻区中执行确定目标邻区对应的邻区指纹库中与目标用户账号对应的邻区下行频谱效率；获取所述目标邻区中下行时隙剩余的可用资源块数；根据所述邻区下行频谱效率和所述可用资源块数确定所述目标邻区中下行时隙的最大发送数据量；根据所述最大发送数据量和所述目标邻区对应的调度下行时隙数预测所述目标用户账号在所述目标邻区的邻区下行感知速率，等步骤。并在确定目标用户账号在所述目标邻区的邻区下行感知速率之后，还会将其发送至服务小区，以便用户通过服务小区知道目标用户账号在所述目标邻区的邻区下行感知速率。
在本实施例中，通过在服务小区或目标邻区中预测目标用户账号在目标邻区的邻区下行感知速率，从而可以保障预测的邻区下行感知速率的有效性。
基于上述本申请的第一至第三任一实施例，提出本申请速率预测方法的第四实施例，在本实施例中，参照图4，速率预测方法，应用于基站，包括：
步骤S100，根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
步骤S200，统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加至所述栅格内，生成邻区指纹库；
步骤S300，基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。
在本实施例中，基站侧可以创建每个小区对应的指纹库，即邻区指纹库。并且在构建完成各个小区的邻区指纹库后，可以进行各个小区之间的邻区指纹库交换，即每个小区都可以存储保留相邻小区的邻区指纹库。
在本实施例中，构建每个小区的邻区指纹库的方式相同，都可以是根据小区内历史用户账号的用户信息进行栅格划分，以得到多个栅格。例如，将收集的终端测量的下行参考信号RSRP、终端测量的下行参考信号SINR、下行路损、芯片类型、位置信息将具有相同特征的用户划分到相同的类别中，每一个类别就是一个栅格，在这些栅格中统计这些用户的下行SE的均值、最大值、最小值、方差等信息。在一实施方式中，可以在进行栅格划分之后，统计隶属于同一栅格内的历史用户信息对应的下行频谱效率，并将此下行频谱效率添加至栅格内，并在各个栅格内都添加完成之后，就将其作为邻区指纹库。以便后续在服务小区或者目标邻区中根据邻区指纹库直接确定目标用户账号在目标邻区的邻区下行感知速率。
历史用户账号的用户信息包括所述历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。例如，历史用户账号的用户信息包括历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量或者邻区下行参考信号的信号与干扰加噪声比。另外为辅助提高邻区指纹库中栅格划分的准确性，历史用户账号的用户信息还可以在历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量或者邻区下行参考信号的信号与干扰加噪声比的基础上，增加邻区下行路损、芯片类型和位置信息等中的至少一种。
在基站确定目标邻区内的邻区指纹库之后，可以直接获取目标用户账号的用户信息，并在邻区指纹库中筛选出与目标用户账号的用户信息匹配的下行频谱效率，再将其发送至服务小区。
此外在一场景中，可以将邻区指纹库发送至服务小区，服务小区基于邻区指纹库确定目标用户账号在目标邻区的邻区下行感知速率。具体地，可以是服务小区从邻区指纹库中筛选出与目标用户账号的用户信息匹配的下行频谱效率，即邻区下行频谱效率，然后在获取目标邻区中下行时隙剩余的可用资源块数，根据可用资源块数和邻区下行频谱效率预测目标邻区中下行时隙的最大发送数据量，再根据最大发送数据量和目标邻区对应的调度下行时隙数预测目标用户账号在目标邻区的邻区下行感知速率。
此外，在一场景中，还可以是在基站检测到服务小区发送的目标用户账号以及目标用 户账号的用户信息之后，将目标用户账号以及目标用户账号的用户信息发送至目标邻区，以便目标邻区根据自身的邻区指纹库和目标用户账号的用户信息确定目标用户账号在目标邻区的邻区下行感知速率，并将邻区下行感知速率反馈至基站，由基站反馈至服务小区。
在本实施例中，通过根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将其添加至栅格内，以生成邻区指纹库，再根据邻区指纹库确定目标用户账号在目标邻区的邻区下行感知速率，从而可以避免通过RSRP、RSRQ、SINR只能获取到邻区下行信道的质量情况，不能完全反应下行感知速率，导致邻区下行感知速率预测的准确性低的现象发生，并且是直接通过目标邻区的邻区指纹库进行预测的，提高了邻区下行感知速率预测的准确性。并且在预测得到目标用户账号在目标邻区的邻区下行感知速率后，可以实现在后续进行切换过程中基于预测的邻区下行感知速率进行切换，以确保用户时刻都处于一个下行感知最优的小区。
此外，本申请还提供一种电子设备，电子设备包括存储器、处理器及存储在存储器上并可在处理器上运行的速率预测程序，速率预测程序被处理器执行时实现如上述的速率预测方法的步骤。
此外，在一实施例中，图6为本申请的一个实施例电子设备的结构示意图，如图6所示，在硬件层面，该电子设备包括处理器，可选地还包括内部总线、网络接口、存储器。其中，存储器可能包含内存，例如高速随机存取存储器(Random-Access Memory，RAM)，也可能还包括非易失性存储器(non-volatile memory)，例如至少1个磁盘存储器等。当然，该电子设备还可能包括其他业务所需要的硬件。处理器、网络接口和存储器可以通过内部总线相互连接，该内部总线可以是ISA(Ind ustry Standa rd Architecture，工业标准体系结构)总线、PCI(Peripheral Component Interconnect，外设部件互连标准)总线或EISA(Extended Industry Standard Architecture，扩展工业标准结构)总线等。所述总线可以分为地址总线、数据总线、控制总线等。为便于表示，图6中仅用一个双向箭头表示，但并不表示仅有一根总线或一种类型的总线。存储器，用于存放程序。程序可以包括程序代码，所述程序代码包括计算机操作指令。处理器从非易失性存储器中读取对应的计算机程序到存储器中然后运行，在逻辑层面上形成共享资源访问控制装置。处理器，执行存储器所存放的程序，并具体用于执行上述速率预测方法的步骤。
本申请电子设备具体实施方式与上述速率预测方法各实施例基本相同，在此不再赘述。
此外，为实现上述目的，本申请还提供一种计算机可读存储介质，计算机可读存储介质上存储有速率预测程序，速率预测程序被处理器执行时实现如上述的速率预测成方法的步骤。
本申请计算机可读存储介质具体实施方式与上述速率预测方法各实施例基本相同，在此不再赘述。
本领域普通技术人员可以理解，上文中所公开方法中的全部或某些步骤、系统、装置中的功能模块/单元可以被实施为软件、固件、硬件及其适当的组合。在硬件实施方式中，在以上描述中提及的功能模块/单元之间的划分不一定对应于物理组件的划分；例如，一个物理组件可以具有多个功能，或者一个功能或步骤可以由若干物理组件合作执行。某些物 理组件或所有物理组件可以被实施为由处理器，如中央处理器、数字信号处理器或微处理器执行的软件，或者被实施为硬件，或者被实施为集成电路，如专用集成电路。这样的软件可以分布在计算机可读介质上，计算机可读介质可以包括计算机存储介质(或非暂时性介质)和通信介质(或暂时性介质)。如本领域普通技术人员公知的，术语计算机存储介质包括在用于存储信息(诸如计算机可读指令、数据结构、程序模块或其他数据)的任何方法或技术中实施的易失性和非易失性、可移除和不可移除介质。计算机存储介质包括但不限于RAM、ROM、EEPROM、闪存或其他存储器技术、CD-ROM、数字多功能盘(DVD)或其他光盘存储、磁盒、磁带、磁盘存储或其他磁存储装置、或者可以用于存储期望的信息并且可以被计算机访问的任何其他的介质。此外，本领域普通技术人员公知的是，通信介质通常包含计算机可读指令、数据结构、程序模块或者诸如载波或其他传输机制之类的调制数据信号中的其他数据，并且可包括任何信息递送介质。
以上仅为本申请的可选实施例，并非因此限制本申请的专利范围，凡是利用本申请说明书及附图内容所作的等效结构或等效流程变换，或直接或间接运用在其他相关的技术领域，均同理包括在本申请的专利保护范围内。

Claims (14)

  1. 一种速率预测方法，应用于服务小区，包括：
    获取目标邻区发送的邻区指纹库，其中，所述邻区指纹库是根据历史用户账号的用户信息进行栅格划分，并统计隶属于同一栅格内的用户信息对应的下行频谱效率，将所述下行频谱效率添加至对应栅格内生成的；
    基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。
  2. 如权利要求1所述的速率预测方法，其中，所述基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率，包括：
    在所述邻区指纹库中筛选出与目标用户账号的用户信息匹配的下行频谱效率，并将匹配的所述下行频谱效率作为邻区下行频谱效率；
    根据所述邻区下行频谱效率预测所述目标用户账号在目标邻区的邻区下行感知速率。
  3. 如权利要求2所述的速率预测方法，其中，所述根据所述邻区下行频谱效率预测所述目标用户账号在目标邻区的邻区下行感知速率，包括：
    获取所述目标邻区中下行时隙剩余的可用资源块数，根据所述邻区下行频谱效率和所述可用资源块数确定所述目标邻区中下行时隙的最大发送数据量；
    根据所述最大发送数据量和所述目标邻区对应的调度下行时隙数预测所述目标用户账号在所述目标邻区的邻区下行感知速率。
  4. 如权利要求3所述的速率预测方法，其中，所述获取所述目标邻区中下行时隙剩余的可用资源块数，包括：
    确定所述目标邻区的剩余资源块数和所述目标邻区中平均每用户账号的第一资源块数；
    选择所述剩余资源块数和所述第一资源块数中数据最高的一个作为所述目标邻区中下行时隙剩余的可用资源块数。
  5. 如权利要求4所述的速率预测方法，其中，所述确定所述目标邻区的剩余资源块数和所述目标邻区中平均每用户账号的第一资源块数，包括：
    确定所述目标邻区的带宽对应的第二资源块数；
    依据所述第二资源块数和所述目标邻区对应的下行资源块利用率确定所述目标邻区的剩余资源块数；
    依据所述第二资源块数和所述目标邻区中的邻区用户账号数确定所述目标邻区中平均每用户账号的第一资源块数。
  6. 如权利要求2所述的速率预测方法，其中，所述根据所述邻区下行频谱效率预测目标用户账号在目标邻区的邻区下行感知速率之后，包括：
    在所述目标邻区存在多个之后，确定所述目标用户账号在每个目标邻区的邻区下行感知速率；
    确定各所述邻区下行感知速率中速率最大的邻区下行感知速率，并选择速率最大的邻区下行感知速率对应的目标邻区进行处理。
  7. 如权利要求1所述的速率预测方法，其中，所述用户信息包括历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。
  8. 一种速率预测方法，应用于目标邻区，包括：
    根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
    统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加至所述栅格内，生成邻区指纹库；
    将所述邻区指纹库发送至服务小区，所述服务小区基于所述邻区指纹库确定所述目标用户账号在所述目标邻区的邻区下行感知速率。
  9. 如权利要求8所述的速率预测方法，其中，所述历史用户账号的用户信息包括所述历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。
  10. 如权利要求8所述的速率预测方法，其中，所述将所述下行频谱效率添加至所述栅格内，生成邻区指纹库之后，还包括：
    接收服务小区发送的目标用户账号以及所述目标用户账号的用户信息，依据所述目标用户账号的用户信息和所述邻区指纹库确定所述目标用户账号在所述目标邻区的邻区下行感知速率，将所述邻区下行感知速率反馈至服务小区。
  11. 一种速率预测方法，应用于基站，包括：
    根据历史用户账号的用户信息进行栅格划分，得到多个栅格；
    统计隶属于同一栅格内的用户信息对应的下行频谱效率，并将所述下行频谱效率添加至所述栅格内，生成邻区指纹库；
    基于所述邻区指纹库确定目标用户账号在所述目标邻区的邻区下行感知速率。
  12. 如权利要求11所述的速率预测方法，其中，所述历史用户账号的用户信息包括所述历史用户账号在目标邻区中的邻区下行参考信号的参考信号接收功率、邻区下行参考信号的参考信号接收质量、邻区下行参考信号的信号与干扰加噪声比、邻区下行路损、芯片类型和位置信息中的至少一种。
  13. 一种电子设备，其中，所述电子设备包括：存储器、处理器及存储在所述存储器上并可在所述处理器上运行的速率预测程序，所述速率预测程序被所述处理器执行时实现如权利要求1至12中任一项所述的速率预测方法的步骤。
  14. 一种计算机可读存储介质，其中，所述计算机可读存储介质上存储有速率预测程序，所述速率预测程序被处理器执行时实现如权利要求1至12中任一项所述的速率预测方法的步骤。
PCT/CN2024/075204 2023-02-20 2024-02-01 速率预测方法、电子设备及计算机可读存储介质 WO2024174830A1 (zh)

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Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101686512A (zh) * 2008-09-23 2010-03-31 大唐移动通信设备有限公司 一种选择目的邻小区的方法和装置
CN104754671A (zh) * 2013-12-31 2015-07-01 中国移动通信集团设计院有限公司 一种异系统小区重选方法、装置和网络侧设备
CN106572540A (zh) * 2016-11-01 2017-04-19 上海华为技术有限公司 一种数据调度方法和接入网设备
CN110366218A (zh) * 2018-04-11 2019-10-22 大唐移动通信设备有限公司 一种小区切换的方法和装置
WO2020125056A1 (zh) * 2018-12-21 2020-06-25 中兴通讯股份有限公司 一种业务的处理方法及装置
CN114554562A (zh) * 2022-04-14 2022-05-27 中国联合网络通信集团有限公司 邻区切换方法、装置、基站及存储介质
CN114928867A (zh) * 2022-06-21 2022-08-19 中国联合网络通信集团有限公司 小区切换方法、装置、电子设备及存储介质

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101686512A (zh) * 2008-09-23 2010-03-31 大唐移动通信设备有限公司 一种选择目的邻小区的方法和装置
CN104754671A (zh) * 2013-12-31 2015-07-01 中国移动通信集团设计院有限公司 一种异系统小区重选方法、装置和网络侧设备
CN106572540A (zh) * 2016-11-01 2017-04-19 上海华为技术有限公司 一种数据调度方法和接入网设备
CN110366218A (zh) * 2018-04-11 2019-10-22 大唐移动通信设备有限公司 一种小区切换的方法和装置
WO2020125056A1 (zh) * 2018-12-21 2020-06-25 中兴通讯股份有限公司 一种业务的处理方法及装置
CN114554562A (zh) * 2022-04-14 2022-05-27 中国联合网络通信集团有限公司 邻区切换方法、装置、基站及存储介质
CN114928867A (zh) * 2022-06-21 2022-08-19 中国联合网络通信集团有限公司 小区切换方法、装置、电子设备及存储介质

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