WO2021109716A1 - 初始mcs值确定方法、电子设备及存储介质 - Google Patents

初始mcs值确定方法、电子设备及存储介质 Download PDF

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WO2021109716A1
WO2021109716A1 PCT/CN2020/120668 CN2020120668W WO2021109716A1 WO 2021109716 A1 WO2021109716 A1 WO 2021109716A1 CN 2020120668 W CN2020120668 W CN 2020120668W WO 2021109716 A1 WO2021109716 A1 WO 2021109716A1
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mcs value
initial
interval
loop
value
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PCT/CN2020/120668
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English (en)
French (fr)
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詹勇
史尚奇
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中兴通讯股份有限公司
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Priority to EP20896204.3A priority Critical patent/EP4072225A4/en
Priority to JP2022534319A priority patent/JP7385039B2/ja
Publication of WO2021109716A1 publication Critical patent/WO2021109716A1/zh

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0015—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy
    • H04L1/0019—Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy in which mode-switching is based on a statistical approach
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04W—WIRELESS COMMUNICATION NETWORKS
    • H04W72/00—Local resource management
    • H04W72/50—Allocation or scheduling criteria for wireless resources
    • H04W72/54—Allocation or scheduling criteria for wireless resources based on quality criteria
    • H04W72/542—Allocation or scheduling criteria for wireless resources based on quality criteria using measured or perceived quality
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0002—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate
    • H04L1/0003—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate by switching between different modulation schemes
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/0001—Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0009—Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the channel coding

Definitions

  • the embodiments of the present application relate to the field of communication technologies, and in particular, to a method for determining an initial MCS value, an electronic device, and a storage medium.
  • AMC Adaptive Modulation and Coding
  • MCS Modulation and Coding Scheme
  • the inner-loop MCS is still determined by the real-time channel quality of the UE, while the outer-loop MCS is gradually adjusted based on the initial outer-loop MCS based on the BLER (Block Error Ratio) of the UE's several data transmissions.
  • BLER Block Error Ratio
  • the purpose of the embodiments of the present application is to provide a method for determining an initial MCS value, an electronic device, and a storage medium.
  • the implementation of the present application provides an initial MCS determination method, including the following steps: determine the current interval of N measurement parameters of the terminal that affect the MCS value of the modulation and coding mechanism; wherein the interval of each measurement parameter passes The possible value ranges of the measurement parameters are divided into intervals in advance; N is a natural number greater than 0; according to the current interval of the N measurement parameters, and the pre-statistical results of the different outer loop MCS values of the N measurement parameters in each interval Distribution probability, real-time calculation of the initial outer-loop MCS value of the terminal; determine the initial MCS value of the terminal according to the initial outer-loop MCS value and the inner-loop MCS value of the terminal.
  • the embodiment of the present application also provides an electronic device, including: at least one processor, and a memory communicatively connected with the at least one processor; wherein the memory stores instructions that can be executed by the at least one processor, and the instructions are executed by at least one processor.
  • Each processor executes, so that at least one processor executes the method for determining the initial MCS value as described above.
  • the embodiment of the present application also provides a computer-readable storage medium that stores a computer program, and when the computer program is executed by a processor, the method for determining the initial MCS value as described above is implemented.
  • Fig. 1 is a flowchart of a method for determining an initial MCS in the first embodiment of the present application
  • FIG. 2 is a flowchart of obtaining the distribution probability of different outer loop MCS values of N measurement parameters in each interval according to the first embodiment of the present application;
  • FIG. 3 is a flowchart of a method for determining an initial MCS in the second embodiment of the present application
  • Fig. 4 is a schematic structural diagram of an electronic device according to a third embodiment of the present application.
  • the purpose of the embodiments of the present application is to provide an initial MCS value determination method, electronic equipment, and storage medium, so that a more appropriate initial MCS value is determined in the adaptive modulation and coding AMC process, so as to achieve faster UE scheduling MCS convergence speed, The purpose of improving the spectrum efficiency of the system.
  • the first embodiment of the present application relates to a method for determining the initial MCS.
  • Fig. 1 The method for determining the initial MCS value in this embodiment is shown in Fig. 1, and includes:
  • Step 101 Determine the current interval of N measurement parameters that affect the MCS value of the modulation and coding mechanism of the terminal; wherein the interval of each measurement parameter is obtained by dividing the possible value range of the measurement parameter in advance; N is a natural number greater than 0.
  • the measurement parameters that affect the MCS value of the modulation and coding mechanism include but are not limited to: Channel Quality Indication (CQI), Sounding Reference Signal (SRS), and SINR (SINR). Signal to Interference-plus-Noise Ratio) or BF (Beam Forming).
  • CQI Channel Quality Indication
  • SRS Sounding Reference Signal
  • SINR SINR
  • BF Beam Forming
  • the value range of each MCS value measurement parameter is divided into several intervals in advance.
  • the interval division method includes but is not limited to dividing the value range evenly according to the system accuracy requirements.
  • i ⁇ 0,...,I-1 ⁇ denote the relative measurement parameter index of the MCS value, where I denotes the number of MCS value measurement parameters.
  • k i ⁇ ⁇ 0,...,K i -1 ⁇ represent the value interval index of the MCS value measurement parameter i, where K i represents the number of MCS value measurement parameter i value intervals.
  • CQI the only MCS value measurement parameter
  • the value range of CQI is (0,1,2,3,4,5,6,7,8,9,10,11,12,13, 14, 15) is equally divided into 4 intervals
  • the selected MCS measurement parameters include: CQI and SRS-SINR.
  • K 0 4
  • K 1 4
  • Step 102 Determine the distribution probability of different outer loop MCS values corresponding to the current interval of the N measurement parameters of the terminal according to the statistical distribution probability of different outer loop MCS values in each interval of the N measurement parameters.
  • the base station pre-records historical data of all UE scheduling MCS values of all users in a certain period of time, performs statistics on the data, and calculates the distribution probability of each measurement parameter in each interval of the value range.
  • FIG. 2 The method for obtaining the distribution probabilities of different outer-loop MCS values of N measurement parameters in each interval in this embodiment is shown in FIG. 2 and includes:
  • Step 201 Determine N measurement parameters and set a sliding time window.
  • the measurement parameters that the base station currently needs to use for the UE scheduling MCS process are selected, and the time length of the sliding time window is set.
  • the length of the sliding time window is generally set according to experience, and an appropriate value T is selected according to the specific working conditions of the base station. For example, a base station with a larger number of UEs can set a smaller value of T, while a base station with a smaller number of UEs can set a lower value of T. Big T value. Setting the time length too long will result in too much sample data.
  • the sample data far away from the current time does not have a good reference value, which will affect the final determined initial MCS value; and Setting the time length too short will result in too little sample data, lower confidence in the distribution probability obtained by statistics, and will also affect the final initial MCS value.
  • Step 202 Count the interval where each MCS value measurement parameter is located for all UEs in each scheduling and the outer loop MCS value of the UE at the scheduling time.
  • the length of the sliding time window is T.
  • the sliding time window represents the period from time tT to time t-1, and reads all UEs recorded by the system during this period to perform MCS The data during scheduling, and the statistics of all UEs during each scheduling, the interval where each MCS value measurement parameter is located and the current outer loop MCS value of the UE at that time. Finally, calculate the probability that the outer loop MCS equals any value when any MCS value measurement parameter belongs to any interval within the current sliding window.
  • Step 203 Calculate the probability that the outer loop MCS is equal to any value when any MCS value measurement parameter belongs to any interval within the sliding time window.
  • t denote the current moment when the MCS determination process is performed
  • m denote the value of the outer loop MCS
  • Statistical sliding time window tT to t-1 Represents the statistical probability that the MCS of the outer loop is equal to m when the UE MCS value measurement parameter i belongs to the interval k i from tT to t-1, that is Calculate the sliding time window, that is, the time period from tT to t-1 Among them, for all time t, all measured slave parameters i, and all values k i of all measured parameters, k i , Established, namely
  • the CQI measurement parameter index value is 0.
  • T the sliding time window time length
  • the current time is t
  • the number of times that all scheduled UE MCS value measurement parameters i belong to the interval k i and the outer loop MCS is equal to m
  • the statistical results are as follows:
  • the index value of the measurement parameter of CQI is 0, and the index value of SRS-SINR is 1.
  • T 200000ms, and count the sliding time window from tT to t-1 with assumed
  • Step 103 Obtain a target outer-loop MCS value that can maximize the sum of the distribution probability of the outer-loop MCS value corresponding to the interval where the N measurement parameters are currently located.
  • the base station first obtains the value of each measurement parameter currently undergoing the MCS value determination process, and then determines the distribution probability of different outer loop MCS values corresponding to the current interval of the current terminal N measurement parameters.
  • the distribution probability corresponding to each MCS value is summed, and the target outer loop MCS value that can maximize the sum of the distribution probability of the outer loop MCS value corresponding to the current interval of the N measurement parameters is obtained.
  • the outer-loop MCS value that can maximize the weighted probability sum of the interval where all the MCS value-related measurement parameters of the UE is located is calculated, and this value is used as the initial outer-loop MCS of the UE.
  • the weight used for weighting can be simply set to 1 divided by the number of measurement parameters related to the MCS value, or the UE can arbitrarily specify the number of samples in the interval where the MCS value related measurement parameters are divided by the total number of samples in the interval where all the measurement parameters related to the MCS value of the UE are located. the amount.
  • the initial MCS of the UE is obtained by combining the real-time calculated MCS value of the inner loop.
  • the target outer-loop MCS value that can maximize the sum of the distribution probability of the outer-loop MCS value corresponding to the current interval of the N measurement parameters can be selected, and a more appropriate one can be selected.
  • Initial MCS so as to achieve the purpose of accelerating the MCS convergence speed of UE scheduling and improving the spectrum efficiency of the system.
  • the target outer loop MCS value corresponding to the element with the largest probability value in the unique measurement parameter distribution probability matrix is directly used as the initial outer loop MCS value.
  • N is greater than 1, then N The matrix is summed, and the summed matrix is obtained Then, the target outer-loop MCS value corresponding to the element with the largest value in the summed matrix is taken as the initial outer-loop MCS value.
  • u denote the UE index, Indicates the interval of the UE uMCS value measurement parameter i at the current moment.
  • calculate the initial outer loop of UE u in real time among them Represents the weight assigned to the MCS value measurement parameter i of the UE identified as u at time t.
  • the value of can be adjusted manually through the parameter interface, or can be automatically calculated according to certain rules. Such as can make or
  • the initial outer-loop MCS of the UE with the identifier 0 is -2
  • the inner-loop MCS of the UE with the identifier 0 is calculated to be 15, so the initial MCS of the UE with the identifier 0 is 13.
  • Step 104 Determine the initial MCS value of the terminal according to the initial outer-loop MCS value and the inner-loop MCS value of the terminal.
  • the inner loop MCS value is determined by the real-time channel quality of the UE, and the initial outer loop MCS value is given based on experience and is often a fixed value.
  • the UE scheduling MCS value is the sum of the inner loop MCS value and the outer loop MCS value.
  • the inner loop MCS value is still determined by the real-time channel quality of the UE, while the outer loop MCS value is gradually adjusted based on the initial outer loop MCS based on the BLER (Block Error Ratio) of the UE's several data transmissions.
  • This embodiment only provides a method for obtaining the initial outer-loop MCS, which speeds up the process of converging the initial outer-loop MCS to the outer-loop MCS.
  • this embodiment calculates in advance the distribution probability of the different outer loop values of the N measurement parameters in each interval, and calculates a more appropriate value in real time according to the distribution probability and the current interval of the current N measurement parameters.
  • the initial MCS outer loop value enables the initial MCS value to quickly converge to a UE scheduling MCS value with a lower bit error rate BLER.
  • the second embodiment of the present application relates to a method for determining the initial MCS value.
  • This embodiment is roughly the same as the first embodiment. The difference is that in this embodiment, before obtaining the target outer-loop MCS value that maximizes the sum of the distribution probability of the outer-loop MCS value corresponding to the interval where the N measurement parameters are currently located , To obtain the weighting coefficient of each measurement parameter.
  • the method for determining the initial MCS value in this embodiment is shown in FIG. 3 and includes:
  • Step 301 Determine the current interval of N measurement parameters that affect the MCS value of the modulation and coding mechanism of the terminal.
  • Step 302 Determine the distribution probability of different outer-loop MCS values corresponding to the current interval of the N measurement parameters of the terminal according to the statistical distribution probabilities of different outer-loop MCS values in each interval of the N measurement parameters.
  • Step 301 and step 302 are similar to step 101 and step 102 in the first embodiment of the present application, and the implementation details have been specifically described in the first embodiment of the present application, and will not be repeated here.
  • Step 303 Obtain the weighting coefficient of each measurement parameter.
  • Step 304 Obtain a target outer loop MCS value that can maximize the weighted sum of the outer loop value distribution probability of the interval where the N measurement parameters are currently located.
  • the weighting coefficient of each measurement parameter is 1/N by default, and the weighting coefficient corresponding to the measurement parameter in this embodiment is Determined according to the number of samples in the interval where the measurement parameters are currently located and the total number of samples in the interval where the N measurement parameters are currently located, where That is to say, the weighting coefficient is equal to the number of samples in the interval where the UE arbitrarily designated MCS value measurement parameters are divided by the number of samples in the interval where all MCS value-related measurement parameters of the UE are located divided by the total number of samples in the interval where all the MCS value measurement parameters of the UE are located.
  • the weighting coefficient can make the calculated initial outer loop MCS value more consistent with scheduling samples, avoid statistical errors caused by too few samples of a certain measurement parameter, and obtain an initial outer loop MCS value with a slower convergence rate.
  • the target outer ring MCS value is determined by the following formula:
  • the weighting coefficient is adjusted in real time through the parameter interface.
  • Step 305 Determine the initial MCS value of the terminal according to the initial outer-loop MCS value and the inner-loop MCS value of the terminal.
  • the third embodiment of the present application relates to an electronic device, as shown in FIG. 4, including:
  • At least one processor 401 and a memory 402 that is communicatively connected with the at least one processor 401; wherein the memory 402 stores instructions executable by the at least one processor 401, and the instructions are executed by the at least one processor 402, so that the At least one processor 401 can execute the initial MCS determination method as in the first embodiment and the second embodiment of this application.
  • the memory and the processor are connected in a bus mode
  • the bus may include any number of interconnected buses and bridges, and the bus connects one or more processors and various circuits of the memory together.
  • the bus can also connect various other circuits such as peripheral devices, voltage regulators, power management circuits, etc., which are all well-known in the art, and therefore, no further description will be given herein.
  • the bus interface provides an interface between the bus and the transceiver.
  • the transceiver may be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on the transmission medium.
  • the data processed by the processor is transmitted on the wireless medium through the antenna, and further, the antenna also receives the data and transmits the data to the processor.
  • the processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions.
  • the memory can be used to store data used by the processor when performing operations.
  • the fourth embodiment of the present application relates to a computer-readable storage medium storing a computer program.
  • the computer program is executed by the processor, the above method embodiment is realized.
  • the program is stored in a storage medium and includes several instructions to enable a device ( It may be a single-chip microcomputer, a chip, etc.) or a processor (processor) that executes all or part of the steps of the methods described in the embodiments of the present application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), magnetic disks or optical disks and other media that can store program codes. .
  • the embodiments of the present application divide the possible value ranges of the measurement parameters in advance to obtain the intervals of each measurement parameter, and calculate the distribution probability of N each measurement parameter in different outer loop MCS values in each interval. First determine the current interval of the measurement parameters of the MCS values of the N modulation and coding mechanisms, calculate the initial outer loop MCS value of the terminal according to the distribution probability, and then obtain the initial MCS value according to the terminal inner loop MCS value and the calculated initial outer loop, so that In the adaptive modulation and coding AMC process, a more appropriate initial MCS value is determined, so as to achieve the purpose of accelerating the convergence speed of the UE scheduling MCS value and improving the system spectrum efficiency.

Abstract

本申请实施例涉及通信技术领域，公开了一种初始MCS值的确定方法。本申请的初始MCS值的确定方法包括：确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间；其中，各测量参数的区间通过预先对测量参数可能的取值范围进行区间划分得到；N为大于0的自然数；根据N个测量参数当前所在区间，以及预先统计得到的N个测量参数在各区间内的不同外环MCS值的分布概率，实时计算终端的初始外环MCS值；根据初始外环MCS值和终端的内环MCS值，确定终端的初始MCS值。

Description

初始MCS值确定方法、电子设备及存储介质
相关申请的交叉引用
本申请基于申请号为201911244259.X、申请日为2019年12月6日的中国专利申请提出，并要求该中国专利申请的优先权，该中国专利申请的全部内容在此以引入方式并入本申请。
技术领域
本申请实施例涉及通信技术领域，特别涉及一种初始MCS值确定方法、电子设备及存储介质。
背景技术
LTE(Long Term Evolution，长期演进)和NR(New Radio,新空口)系统中，AMC(Adaptive Modulation and Coding自适应调制编码)用于确定MCS(Modulation and Coding Scheme调制编码机制)。AMC的过程就是根据信道条件的变化，动态的选择适当MCS的过程。通常情况下，UE的初始MCS＝内环MCS+初始外环MCS。其中，内环MCS由UE实时信道质量决定，而初始外环MCS则根据经验给出，常为固定值。实时调度过程中，UE调度MCS＝内环MCS+外环MCS。其中，内环MCS仍由UE实时信道质量决定，而外环MCS则在初始外环MCS基础上，根据UE数次数据传输BLER(Block Error Ratio块误码率)逐步调整。
以上相关技术中至少存在如下问题：实际系统中，UE初始MCS和其最终收敛后的调度MCS常常相差较大，影响了MCS值最终确定以后的BLER，使用户体验较差。
发明内容
本申请实施方式的目的在于提供一种初始MCS值确定方法、电子设备及存储介质。
为解决上述技术问题，本申请的实施方式提供了一种初始MCS确定方法，包括以下步骤：确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间；其中，各测量参数的区间通过预先对测量参数可能的取值范围进行区间划分得到；N为大于0的自然数；根据N个测量参数当前所在区间，以及预先统计得到的N个测量参数在各区间内的不同外环MCS值的分布概率，实时计算终端的初始外环MCS值；根据初始外环MCS值和终端的内环MCS值，确定终端的初始MCS值。
本申请的实施方式还提供了一种电子设备，包括：至少一个处理器，以及与至少一个处理器通信连接的存储器；其中，存储器存储有可被至少一个处理器执行的指令，指令被至少一各处理器执行，以使至少一个处理器执行如上述的初始MCS值的确定方法。
本申请的实施方式还提供了一种计算机可读存储介质，存储有计算机程序，计算机程序被处理器执行时实现如上述的初始MCS值的确定方法。
附图说明
一个或多个实施例通过与之对应的附图中的图片进行示例性说明，这些示例性说明并不构成对实施例的限定，附图中具有相同参考数字标号的元件表示为类似的元件，除非有特别申明，附图中的图不构成比例限制。
图1是根据本申请第一实施方式中初始MCS确定方法的流程图；
图2是根据本申请第一实施方式中获取N个测量参数在各区间内的不同外环MCS值的分布概率的流程图；
图3是根据本申请第二实施方式中初始MCS确定方法的流程图；
图4是根据本申请第三实施方式中电子设备的结构示意图。
具体实施方式
为使本申请实施例的目的、技术方案和优点更加清楚，下面将结合附图对本申请的各实施方式进行详细的阐述。然而，本领域的普通技术人员可以理解，在本申请各实施方式中，为了使读者更好地理解本申请而提出了许多技术细节。但是，即使没有这些技术细节和基于以下各实施方式的种种变化和修改，也可以实现本申请所要求保护的技术方案。以下各个实施例的划分是为了描述方便，不应对本申请的具体实现方式构成任何限定，各个实施例在不矛盾的前提下可以相互结合相互引用。
本申请实施方式的目的在于提供一种初始MCS值确定方法、电子设备及存储介质，使得在自适应调制编码AMC过程中，确定一个更加合适的初始MCS值，从而实现加快UE调度MCS收敛速度、提高系统频谱效率的目的。
本申请的第一实施方式涉及一种初始MCS的确定方法。在本实施方式中，确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间；其中，各测量参数的区间通过预先对测量参数可能的取值范围进行区间划分得到；N为大于0的自然数；根据N个测量参数当前所在区间，以及预先统计得到的N个测量参数在各区间内的不同外环MCS值的分布概率，实时计算终端的初始外环MCS值；根据初始外环MCS值和终端的内环MCS值，确定终端的初始MCS值。
下面对本实施方式的初始MCS值的确定方法的实现细节进行具体的说明，以下内容仅为方便理解提供的实现细节，并非实施本方案的必须。
本实施方式中的初始MCS值的确定方法如图1所示，包括：
步骤101，确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间；其中，各测量参数的区间通过预先对测量参数可能的取值范围进行区间划分得到；N为大于0的自然数。
具体的说，在本实施方式中，影响调制编码机制MCS值的测量参数包括但不限于：信道质量指示CQI(Channel Quality Indication)、探寻参考信号SRS(Sounding Reference Signal)、信号干扰噪声比SINR(Signal to Interference-plus-Noise Ratio)或波束赋形增益BF(Beam Forming)。预先将每个MCS值测量参数取值范围划分为数个区间，区间划分方法包括但不限于将其取值范围按照系统精确度要求均匀划分。当基站开始进行UE的MCS值的确定过程时，选择其中至少一个，或任意个参数的组合来作为影响调制编码机制 MCS值的测量参数，然后确定所选择的参数当前的取值在哪一个区间内。令i∈{0,…,I-1}表示MCS值的相关测量参数索引，其中I表示MCS值测量参数的个数。同时令k i∈{0,…,K i-1}表示MCS值的测量参数i取值区间索引，其中K i表示MCS值测量参数i取值区间的个数。
在一个例子中，取CQI为唯一MCS值测量参数，假定CQI的取值范围为(0，1，2，3，4，5，6，7，8，9，10，11，12，13，14，15)被均分为4个区间，则k 0∈{0,…,3}，K 0＝10，即具体划分方法为当CQI∈{0,1,2,3}时，索引值k 0＝0；当CQI∈{4,5,6,7}时，索引值k 0＝1；当CQI∈{8,9,10,11}时，索引值k 0＝2；当CQI∈{12,13,14,15,}时，索引值k 0＝3。
在另一个例子中，选取的MCS测量参数包括：CQI、及SRS-SINR。此时i∈{0,1}表示MCS值测量参数索引，I＝2。令k 0∈{0,…,3}，此时K 0＝4。具体区间划分方法为k 0＝0，即当CQI∈{0,1,2,3}，k 0＝1，即当CQI∈{4,5,6,7}，k 0＝2，当CQI∈{8,9,10,11}，k 0＝3，即当CQI∈{12,13,14,15}。令k 1∈{0,…,3}，此时K 1＝4。具体区间划分方法为k 1＝0，即当SRS-SINR≤10dB，k 1＝1，即当10dB<SRS-SINR≤15dB，k 1＝2，即当15dB<SRS-SINR≤20dB，k 1＝3，即当SRS-SINR>20dB。
步骤102，根据统计的N个测量参数在各区间内的不同外环MCS值的分布概率，确定终端的N个测量参数当前所在区间对应的不同外环MCS值的分布概率。
具体的说，基站预先记录某一时间段所有用户UE调度MCS值的历史数据，对数据进行统计，计算出各个测量参数在取值范围的各区间里的分布概率。
本实施方式中的获取N个测量参数在各区间内的不同外环MCS值的分布概率的方法如图2所示，包括：
步骤201，确定N个测量参数并设置滑动时间窗。
具体的说，选定基站当前进行UE调度MCS过程所需要使用的测量参数，并设定滑动时间窗的时间长度。滑动时间窗的长度一般根据经验来进行设置，根据基站的具体工作状况取一个合适的值T，比如UE数量较大的基站可以设置较小的T值，而UE数量较小的基站可以设置较大的T值。时间长度设置过长会导致样本数据过多，由于基站在不同时间段的工作压力不同，因此距当前时刻较远的样本数据不具有较好的参考价值，从而影响最终确定的初始MCS值； 而时间长度设置过短则会导致样本数据过少，统计得到的分布概率置信度较低，也会影响最终确定的初始MCS值。
步骤202，统计所有UE在每一次调度中每个MCS值测量参数所在区间和该UE在调度时刻的外环MCS值。
具体的说，滑动时间窗的时长为T，对于当前时刻t而言，滑动时间窗表示t-T时刻到t-1时刻的这一段时间，读取系统在这段时间内记录的所有的UE进行MCS调度时的数据，并分别统计所有UE在每次调度时，其每个MCS值测量参数所在区间和该UE当时外环MCS值。最终计算得出当前滑窗内，任一MCS值测量参数归属于任一区间时，外环MCS等于任一值的概率。
步骤203，计算出在滑动时间窗内，任一MCS值测量参数归属于任一区间时，外环MCS等于任一值的概率。
具体的说，本实施方式中，令t表示进行MCS确定过程的当前时刻，m表示外环MCS取值，
Figure PCTCN2020120668-appb-000001
表示从t-T时刻到t-1时刻，也就是滑动时间窗内，所有UE调度MCS值测量参数i归属于区间k i的次数，
Figure PCTCN2020120668-appb-000002
表示滑动时间窗内所有UE调度MCS值测量参数i归属于区间k i且外环MCS等于m的次数。统计滑动时间窗t-T到t-1内
Figure PCTCN2020120668-appb-000003
和
Figure PCTCN2020120668-appb-000004
令
Figure PCTCN2020120668-appb-000005
表示从t-T到t-1时刻，当调度UE MCS值测量参数i归属于区间k i时，外环MCS等于m的统计概率，即
Figure PCTCN2020120668-appb-000006
计算得到滑动时间窗，即t-T到t-1时间段内的
Figure PCTCN2020120668-appb-000007
其中，对所有的时刻t、所有测量从参数i以及所有测量参数的所有取值k i，都使得k i,
Figure PCTCN2020120668-appb-000008
成立，即
Figure PCTCN2020120668-appb-000009
以取CQI为唯一MCS值测量参数为例，CQI的测量参数索引值为0。取滑动时间窗时间长度T＝200000ms，当前时刻为t，则统计在t-T到t-1时间段内的所有UE调度MCS值测量参数i归属于区间k i的次数
Figure PCTCN2020120668-appb-000010
以及所有调度UE MCS值测量参数i归属于区间k i且外环MCS等于m的次数
Figure PCTCN2020120668-appb-000011
假设统计结果如下：
Figure PCTCN2020120668-appb-000012
Figure PCTCN2020120668-appb-000013
通过计算得到滑动时间窗内的
Figure PCTCN2020120668-appb-000014
Figure PCTCN2020120668-appb-000015
以测量参数包括：CQI、及SRS-SINR为例，CQI的测量参数索引值为0、SRS-SINR的索引值为1。取T＝200000ms，并统计滑动时间窗t-T到t-1时间段内的
Figure PCTCN2020120668-appb-000016
和
Figure PCTCN2020120668-appb-000017
假定
Figure PCTCN2020120668-appb-000018
Figure PCTCN2020120668-appb-000019
Figure PCTCN2020120668-appb-000020
Figure PCTCN2020120668-appb-000021
计算得到滑动时间窗内
Figure PCTCN2020120668-appb-000022
Figure PCTCN2020120668-appb-000023
步骤103，获取能够最大化N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值。
具体的说，基站首先获取当前进行MCS值确定过程的各测量参数的取值，然后确定当前终端的N个测量参数当前所在区间对应的不同外环MCS值的分布概率。对各个MCS值所对应的分布概率进行求和，获取能够最大化N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值。得 到UE每个MCS值相关测量参数所在区间对应的不同外环MCS值的统计概率。计算得到能够最大化该UE所有MCS值相关测量参数所在区间加权概率和的外环MCS值，将此值作为该UE初始外环MCS。加权所用权值可以简单的设为1除以MCS值相关测量参数个数，也可以使用该UE任意指定MCS值相关测量参数所在区间样本数量除以该UE所有MCS值相关测量参数所在区间样本总量。最终，结合实时计算的内环MCS值，得到UE初始MCS。
通过对系统在滑动时间窗内历史调度样本的学习，取用能够最大化N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值，能够选定一个更加合适的初始MCS，从而达到加快UE调度MCS收敛速度、提高系统频谱效率的目的。
当N等于1时，直接以该唯一测量参数分布概率矩阵中概率值最大的元素所对应的目标外环MCS值作为初始外环MCS值。当N大于1时，则将N个
Figure PCTCN2020120668-appb-000024
矩阵进行求和，得到求和后的矩阵
Figure PCTCN2020120668-appb-000025
然后以求和后的矩阵中取值最大的元素所对应的目标外环MCS值作为初始外环MCS值。令u表示UE索引，
Figure PCTCN2020120668-appb-000026
表示当前时刻UE uMCS值测量参数i所在区间。在时刻t，实时计算UE u初始外环
Figure PCTCN2020120668-appb-000027
其中
Figure PCTCN2020120668-appb-000028
代表时刻t给标识为u的UE的MCS值测量参数i所赋权重。另外，
Figure PCTCN2020120668-appb-000029
的取值可通过参数接口人工调整，也可根据一定规则自动计算。比如可令
Figure PCTCN2020120668-appb-000030
或
Figure PCTCN2020120668-appb-000031
以取CQI为唯一MCS值测量参数为例，假定标识为0的UE在时刻t的CQI＝10，即
Figure PCTCN2020120668-appb-000032
然后令
Figure PCTCN2020120668-appb-000033
Figure PCTCN2020120668-appb-000034
即令UE 0初始外环MCS为-3，计算得到UE0内环MCS为15，因此UE 0初始MCS为12。假设UE 1在时刻t CQI＝14，即
Figure PCTCN2020120668-appb-000035
即令UE 1初始外环MCS为-1， 计算得到UE 1内环MCS为24，因此UE 1初始MCS为23。
以测量参数包括：CQI和SRS_SINR为例，假设标识为0的UE在时刻t CQI＝10，即
Figure PCTCN2020120668-appb-000036
SRS_SINR＝16dB，即
Figure PCTCN2020120668-appb-000037
令
Figure PCTCN2020120668-appb-000038
Figure PCTCN2020120668-appb-000039
则
Figure PCTCN2020120668-appb-000040
Figure PCTCN2020120668-appb-000041
即令标识为0的UE的初始外环MCS为-2，计算得到标识为0的UE的内环MCS为15，因此标识为0的UE初始MCS为13。假设标识为1的UE在时刻t CQI＝14，即
Figure PCTCN2020120668-appb-000042
SRS-SINR＝19dB，即
Figure PCTCN2020120668-appb-000043
此时
Figure PCTCN2020120668-appb-000044
Figure PCTCN2020120668-appb-000045
其中
Figure PCTCN2020120668-appb-000046
即令UE 1初始外环MCS为-2，计算得到标识为1的UE的内环MCS为24，因此标识为1的UE的初始MCS值为22。
步骤104，根据初始外环MCS值和终端的内环MCS值，确定终端的初始MCS值。
具体的说，用户UE的初始MCS值为内环MCS值与初始外环MCS值之和。即标识为u的UE初始MCS＝内环MCS+初始外环MCS。其中，内环MCS值由UE实时信道质量决定，而初始外环MCS值则根据经验给出，常为固定值。实时调度过程中，UE调度MCS值为内环MCS值与外环MCS值之和。其中，内环MCS值仍由UE实时信道质量决定，而外环MCS值则在初始外环MCS基础上，根据UE数次数据传输BLER(Block Error Ratio块误码率)逐步调整。本实施方式仅提供得到初始外环MCS的方法，加快初始外环MCS收敛至外环MCS的过程。与现有技术相比，本实施例通过预先对N个测量参数在各区间内不同外环值的分布概率进行统计，根据分布概率以及当前N个测量参数当前所在区间来实时计算出更加合适的初始MCS外环值从而使得初始MCS值能够快 速收敛于一个误码率BLER较低的UE调度MCS值。
本申请的第二实施方式涉及一种初始MCS值确定方法。本实施方式与第一实施方式大致相同，区别之处在于，本实施方式中，在获取能够最大化N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值之前，获取各测量参数的的加权系数。
本实施方式中的初始MCS值的确定方法如图3所示，包括：
步骤301，确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间。
步骤302，根据统计的N个测量参数在各区间内的不同外环MCS值的分布概率，确定终端的N个测量参数当前所在区间对应的不同外环MCS值的分布概率。
步骤301和步骤302与本申请第一实施方式中的步骤101和步骤102类似，的实施细节已在本申请第一实施方式中具体说明，在此不再赘述。
步骤303，获取各测量参数的加权系数。
步骤304，获取能够最大化N个测量参数当前所在区间的外环值分布概率加权后之和的目标外环MCS值。
具体的说，默认各测量参数的加权系数为1/N，本实施方式中的测量参数对应的加权系数
Figure PCTCN2020120668-appb-000047
根据所述测量参数当前所在区间的样本数量与所述N个测量参数当前所在区间的样本总量确定，其中
Figure PCTCN2020120668-appb-000048
也就是说加权系数等于该UE任意指定MCS值测量参数所在区间样本数量除以该UE所有MCS值相关测量参数所在区间样本数量除以该UE所有MCS值测量参数所在区间样本总量，通过这样的加权系数可以使得计算得到的初始外环MCS值能够与调度样本更加吻合，避免由于某一测量参数样本数量过少而造成的统计误差，从而得到一个收敛速度较慢的初始外环MCS值。
在一个例子中，目标外环MCS值通过以下公式确定：
Figure PCTCN2020120668-appb-000049
另外，加权系数通过参数接口实时调整。
步骤305，根据初始外环MCS值和终端的内环MCS值，确定终端的初始MCS值。
需要说明的是，本实施方式中的上述各示例均为方便理解进行的举例说明，并不对本申请的技术方案构成限定。
上面各种方法的步骤划分，只是为了描述清楚，实现时可以合并为一个步骤或者对某些步骤进行拆分，分解为多个步骤，只要包括相同的逻辑关系，都在本专利的保护范围内；对算法中或者流程中添加无关紧要的修改或者引入无关紧要的设计，但不改变其算法和流程的核心设计都在该专利的保护范围内。
本申请第三实施方式涉及一种电子设备，如图4所示，包括：
至少一个处理器401；以及，与至少一个处理器401通信连接的存储器402；其中，存储器402存储有可被至少一个处理器401执行的指令，指令被至少一个处理器402执行，以使所述至少一个处理器401能够执行如本申请第一实施方式及第二实施方式中的初始MCS确定方法。
其中，存储器和处理器采用总线方式连接，总线可以包括任意数量的互联的总线和桥，总线将一个或多个处理器和存储器的各种电路连接在一起。总线还可以将诸如外围设备、稳压器和功率管理电路等之类的各种其他电路连接在一起，这些都是本领域所公知的，因此，本文不再对其进行进一步描述。总线接口在总线和收发机之间提供接口。收发机可以是一个元件，也可以是多个元件，比如多个接收器和发送器，提供用于在传输介质上与各种其他装置通信的单元。经处理器处理的数据通过天线在无线介质上进行传输，进一步，天线还接收数据并将数据传送给处理器。
处理器负责管理总线和通常的处理，还可以提供各种功能，包括定时，外围接口，电压调节、电源管理以及其他控制功能。而存储器可以被用于存储处理器在执行操作时所使用的数据。
本申请第四实施方式涉及一种计算机可读存储介质，存储有计算机程序。计算机程序被处理器执行时实现上述方法实施例。
即，本领域技术人员可以理解，实现上述实施例方法中的全部或部分步骤 是可以通过程序来指令相关的硬件来完成，该程序存储在一个存储介质中，包括若干指令用以使得一个设备(可以是单片机，芯片等)或处理器(processor)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、磁碟或者光盘等各种可以存储程序代码的介质。
本申请实施方式相对于相关技术而言，预先对测量参数可能的取值范围进行区间划分得到各测量参数的区间，并统计N各测量参数在各区间内不同外环MCS值的分布概率。首先确定N个调制编码机制MCS值的测量参数当前所在区间，根据分布概率计算出终端的初始外环MCS值，然后根据终端内环MCS值和计算出的初始外环得到初始MCS值，使得在自适应调制编码AMC过程中，确定一个更加合适的初始MCS值，从而实现加快UE调度MCS值收敛速度、提高系统频谱效率的目的。
本领域的普通技术人员可以理解，上述各实施方式是实现本申请的具体实施例，而在实际应用中，可以在形式上和细节上对其作各种改变，而不偏离本申请的精神和范围。

Claims (10)

  1. 一种初始调制编码机制MCS值的确定方法，包括：
    确定终端的N个影响调制编码机制MCS值的测量参数当前所在区间；其中，各所述测量参数的区间通过预对所述测量参数可能的取值范围进行区间划分得到；所述N为大于0的自然数；
    根据所述N个测量参数当前所在区间，以及统计得到的所述N个测量参数在各区间内的不同外环MCS值的分布概率，实时计算所述终端的初始外环MCS值；
    根据所述初始外环MCS值和所述终端的内环MCS值，确定所述终端的初始MCS值。
  2. 根据权利要求1所述的初始MCS值的确定方法，其中，所述N个测量参数在各区间内的不同外环MCS值的分布概率，通过以下方式统计得到：
    在预设长度的滑动时间窗内，分别统计所有终端在每次调度时，各所述测量参数所在区间和对应的外环MCS值，得到所述测量参数归属于任一区间时，外环MCS值为任一值的概率。
  3. 根据权利要求1所述的初始MCS值的确定方法，其中，所述根据所述N个测量参数当前所在区间，以及预先统计得到的所述N个测量参数在各区间内的不同外环MCS值的分布概率，实时计算所述终端的初始外环MCS值，包括：
    根据统计的所述N个测量参数在各区间内的不同外环MCS值的分布概率，确定所述终端的所述N个测量参数当前所在区间对应的不同外环MCS值的分布概率；
    获取能够最大化所述N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值；
    将所述目标外环MCS值作为所述终端的初始外环MCS值。
  4. 根据权利要求3所述的初始MCS值的确定方法，其中，所述N个测量参数分别对应一加权系数；
    所述获取能够最大化所述N个测量参数当前所在区间对应的外环MCS 值分布概率之和的目标外环MCS值，包括：
    获取能够最大化经加权后的所述N个测量参数当前所在区间对应的外环MCS值分布概率之和的目标外环MCS值。
  5. 根据权利要求4所述的初始MCS值的确定方法，其中，所述加权系数通过参数接口实时调整。
  6. 根据权利要求4所述的初始MCS值的确定方法，其中，所述测量参数对应的加权系数均为1/N；或者，所述测量参数对应的加权系数根据所述测量参数当前所在区间的样本数量与所述N个测量参数当前所在区间的样本总量确定。
  7. 根据权利要求1至6中任一项所述的初始MCS值的确定方法，其中，所述N个测量参数包括以下之一或其任意组合：信道质量指示、探寻参考信号、信号干扰噪声比或波束赋形增益。
  8. 根据权利要求1至6中任一项所述的初始MCS值的确定方法，其中，所述根据所述初始外环MCS值和所述终端的内环MCS值，确定所述终端的初始MCS值，包括：
    对所述初始外环MCS值和所述终端的内环MCS值进行求和，得到所述终端的初始MCS值；其中，所述内环MCS值根据所述终端的实时信道质量确定。
  9. 一种电子设备，包括：
    至少一个处理器；以及，
    与所述至少一个处理器通信连接的存储器；其中，
    所述存储器存储有可被所述至少一个处理器执行的指令，所述指令被所述至少一个处理器执行，以使所述至少一个处理器能够执行如权利要求1至8中任一所述的初始MCS值的确定方法。
  10. 一种计算机可读存储介质，存储有计算机程序，其中，所述计算机程序被处理器执行时实现权利要求1至8中任一项所述的初始MCS值的确定方法。
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