WO2013040753A1 - 一种mimo sd接收机及其选择mcs的方法 - Google Patents

一种mimo sd接收机及其选择mcs的方法 Download PDF

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Publication number
WO2013040753A1
WO2013040753A1 PCT/CN2011/079870 CN2011079870W WO2013040753A1 WO 2013040753 A1 WO2013040753 A1 WO 2013040753A1 CN 2011079870 W CN2011079870 W CN 2011079870W WO 2013040753 A1 WO2013040753 A1 WO 2013040753A1
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mcs
value
algorithm
sinr
independent signal
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PCT/CN2011/079870
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English (en)
French (fr)
Inventor
胡艳辉
任天民
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中兴通讯股份有限公司
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Priority to PCT/CN2011/079870 priority Critical patent/WO2013040753A1/zh
Publication of WO2013040753A1 publication Critical patent/WO2013040753A1/zh

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    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00Arrangements for detecting or preventing errors in the information received
    • H04L1/0001Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0015Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy
    • H04L1/0016Systems modifying transmission characteristics according to link quality, e.g. power backoff characterised by the adaptation strategy involving special memory structures, e.g. look-up tables
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04BTRANSMISSION
    • H04B7/00Radio transmission systems, i.e. using radiation field
    • H04B7/02Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/08Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H04B7/0837Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station using pre-detection combining
    • H04B7/0842Weighted combining
    • H04B7/0848Joint weighting
    • H04B7/0854Joint weighting using error minimizing algorithms, e.g. minimum mean squared error [MMSE], "cross-correlation" or matrix inversion
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00Arrangements for detecting or preventing errors in the information received
    • H04L1/0001Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0002Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate
    • H04L1/0003Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the transmission rate by switching between different modulation schemes
    • HELECTRICITY
    • H04ELECTRIC COMMUNICATION TECHNIQUE
    • H04LTRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00Arrangements for detecting or preventing errors in the information received
    • H04L1/0001Systems modifying transmission characteristics according to link quality, e.g. power backoff
    • H04L1/0009Systems modifying transmission characteristics according to link quality, e.g. power backoff by adapting the channel coding

Definitions

  • Embodiments of the present invention relate to a wireless communication system, and more particularly to a MIMO SD receiver and a method of selecting the same. Background technique
  • Typical wireless channels are randomly varying, characterized by frequency selectivity and time-varying.
  • the randomness of such wireless channels needs to be taken into account, and a more superior design can exploit this randomness to improve the performance and capacity of wireless communication systems.
  • One of the important ideas is to change the transmission rate by dynamically selecting the Modulation and Coding Scheme (MCS) according to the instantaneous quality of the channel.
  • MCS Modulation and Coding Scheme
  • the dynamic selection technology of MCS is 3G, 4G and even future broadband wireless communication.
  • the key technologies are widely used in LTE and WiMAX fields.
  • the dynamic selection technology of MCS requires the transmitter to have the instantaneous quality information of the channel, and the instant quality information can be obtained through feedback from the receiver. In practical applications, in order to reduce the feedback overhead, the receiving opportunity selects the MCS through channel estimation, and feeds the selected MCS to the transmitter for use.
  • the MIMO (Multiple Input Multiple Output) technology can effectively improve the capacity of the system and the reliability of the wireless channel.
  • multiple independent signals can be transmitted, thus obtaining significant channel capacity gain.
  • the maximum number of independent signals is equal to the smaller of the number of transmitting antennas and the number of receiving antennas. After multiple independent signals pass through the channel, they interfere with each other at the receiver.
  • the receiving performance of each independent signal depends on the ratio of signal power and noise power (including interference power).
  • the mutual interference between independent signals is for each independent signal channel.
  • the receiver's algorithm can be divided into linear algorithm and nonlinear algorithm.
  • MMSE Minimum Mean Squared Error
  • SINR Signal to Interference plus Noise Ratio
  • the main objective of the embodiments of the present invention is to provide a MIMO SD receiver and a method for selecting the MCS.
  • the MIMO SD receiver can accurately select the MCS value, thereby improving the capacity of the system and the reliability of the channel.
  • the present invention provides a MIMO SD receiver, including: a storage module, an MMSE algorithm module, a spatial correlation estimation module, and an adjustment amount calculation module;
  • a storage module configured to save a configured SINR and MCS correspondence table and an SD algorithm MCS adjustment scale
  • MMSE algorithm module which is used to calculate the SINR value of the independent signal, and by querying the SINR and
  • the MCS correspondence table obtains the MCS value of the independent signal
  • a spatial correlation estimation module for calculating spatial correlation
  • the adjustment amount calculation module is configured to obtain the MCS adjustment amount of the SD algorithm by querying the SD algorithm MCS adjustment scale according to the SINR value and the spatial correlation of the independent signal; and also for adjusting the MCS value of the independent signal and the MCS of the SD algorithm according to the independent signal Quantity, calculate the MCS value under the SD algorithm.
  • the correspondence table between the SINR and the MCS is a mapping relationship between the MCS value of each independent signal and the SINR value of each independent signal in the MMSE algorithm;
  • the SD algorithm adjusts the SINR interval for each row in the MCS adjustment scale, and the spatial correlation interval for each column, ⁇ according to a SINR interval and a spatial correlation interval, determines the MCS of the SD algorithm of the SINR interval and the spatial correlation interval. Adjustment amount.
  • the MMSE algorithm module is specifically configured to: calculate a channel estimation value, calculate an SINR value of the independent signal of the MMSE algorithm according to the channel estimation value, and perform the SINR and the MCS according to the SINR value of the independent signal.
  • the query in the corresponding table obtains the MCS value of the independent signal of the corresponding MMSE algorithm.
  • the spatial correlation estimation module is specifically configured to: calculate a determinant value of the spatial channel according to the channel estimation value, and determine a spatial correlation according to the determinant value of the spatial channel.
  • the adjustment amount calculation module is specifically configured to:
  • the MIMO SD receiver queries the SD algorithm MCS adjustment scale to find the SINR value of the independent signal and the MCS adjustment amount of the SD algorithm uniquely determined by the spatial correlation;
  • the MCS value of the independent signal is added to the MCS adjustment of the SD algorithm to obtain the MCS value under the SD algorithm.
  • the present invention also provides a method for selecting a MCS by a MIMO SD receiver, including: configuring a correspondence table between SINR and MCS and an SD algorithm MCS adjustment scale;
  • the MCS adjustment scale obtains the MCS adjustment of the SD algorithm
  • the correspondence table between the SINR and the MCS is an independent letter under the MMSE algorithm.
  • the SD algorithm adjusts the SINR interval for each row in the MCS adjustment scale, and the spatial correlation interval for each column, ⁇ according to a SINR interval and a spatial correlation interval, determines the MCS of the SD algorithm of the SINR interval and the spatial correlation interval. Adjustment amount.
  • the SINR value of the independent signal is calculated, and the MCS value of the independent signal is obtained by querying a correspondence table between the SINR and the MCS:
  • the MIMO SD receiver calculates a channel estimation value, calculates an SINR value of the independent signal of the MMSE algorithm according to the channel estimation value, and queries the corresponding table of the SINR and the MCS according to the SINR value of the independent signal to obtain a corresponding The MCS value of the independent signal under the MMSE algorithm.
  • the computing spatial correlation is:
  • the MIMO SD receiver calculates the determinant value of the spatial channel based on the channel estimation value, and determines the spatial correlation based on the determinant value of the spatial channel.
  • the spatial correlation is determined according to the determinant value of the spatial channel: the spatial correlation is equal to ⁇ IHnl/N, where ⁇ is the total number of subcarriers used to calculate the spatial channel correlation, and ⁇ ⁇ is one The accumulated value of the determinant value of the spatial channel on the carrier, ⁇ is the channel transmission matrix on each subcarrier.
  • the MCS adjustment amount of the SD algorithm is obtained by querying the SD algorithm MCS adjustment scale:
  • the MIMO SD receiver queries the SD algorithm MCS adjustment scale to find the SINR value of the independent signal and the MCS adjustment of the SD algorithm that is uniquely determined by the spatial correlation.
  • the MCS value under the SD algorithm is calculated according to the MCS value of the independent signal and the MCS adjustment amount of the SD algorithm:
  • the MIMO SD receiver uses the MCS value and SD algorithm of the independent signal under the MMSE algorithm.
  • the MCS adjustments are added together to obtain the MCS value under the SD algorithm.
  • the MIMO SD receiver and the method for selecting the MCS configure a correspondence table between the SINR and the MCS and an MCS adjustment scale of the SD algorithm; calculate a SINR (Signal to Interference plus Noise Ratio) value of the independent signal, and query
  • the SINR and MCS correspondence table obtains the MCS value of the independent signal; calculates the spatial correlation, according to the SINR (Signal to Interference plus Noise Ratio) value and spatial correlation of the independent signal, obtains the SD algorithm by querying the SD algorithm MCS adjustment scale MCS adjustment amount; calculating the MCS value under the SD algorithm according to the MCS value of the independent signal and the MCS adjustment amount of the SD algorithm, so in the embodiment of the present invention, according to the spatial correlation of the channel and the SINR (signal to interference plus noise ratio) value Selecting the MCS value of the MIMO MMSE receiver to obtain the MCS value of the MIMO SD receiver, that is, the MIMO SD receiver can accurately select the MCS value, thereby improving the capacity of
  • FIG. 1 is a schematic structural diagram of implementing a MIMO SD receiver according to an embodiment of the present invention
  • FIG. 2 is a schematic flow chart of a method for implementing a MIMO SD receiver to select an MCS according to an embodiment of the present invention. detailed description
  • the storage module saves the correspondence table between the SINR and the MCS and the SD algorithm MCS adjustment scale;
  • the MMSE algorithm module calculates the SINR (signal to interference plus noise ratio) value of the independent signal, and queries the SINR and
  • the MCS correspondence table obtains the MCS value of the independent signal;
  • the spatial correlation estimation mode calculates the spatial correlation, and the adjustment amount calculation module queries the SD algorithm MCS according to the SINR (signal to interference plus noise ratio) value and spatial correlation of the independent signal.
  • the MCS adjustment amount of the SD algorithm is obtained by adjusting the scale;
  • the MCS value under the SD algorithm is calculated according to the MCS value of the independent signal and the MCS adjustment amount of the SD algorithm.
  • FIG. 1 is a schematic structural diagram of a MIMO SD receiver according to an embodiment of the present invention.
  • the apparatus includes: a storage module 11, an MMSE algorithm module 12, and spatial correlation.
  • the MMSE algorithm module 12 is configured to calculate an SINR (Signal to Interference plus Noise Ratio) value of the independent signal, and obtain an MCS value of the independent signal by querying a correspondence table between the SINR and the MCS;
  • the spatial correlation estimation module 13 is configured to calculate a space Correlation;
  • the adjustment amount calculation module 14 is configured to obtain the MCS adjustment amount of the SD algorithm by querying the SD algorithm MCS adjustment scale according to the SINR (Signal to Interference plus Noise Ratio) value and spatial correlation of the independent signal; and also for, according to the independent signal.
  • SINR Signal to Interference plus Noise Ratio
  • the correspondence table between the SINR and the MCS is a mapping relationship between the MCS value of each independent signal and the corresponding SINR (Signal to Interference plus Noise Ratio) value of each independent signal under the MMSE algorithm.
  • Each row in the SD algorithm MCS adjustment scale corresponds to an SINR (Signal to Interference plus Noise Ratio) interval
  • each column corresponds to a spatial correlation interval, according to an SINR (Signal to Interference plus Noise Ratio) interval and a spatial correlation interval
  • the MCS adjustment amount of the SD algorithm of the SINR (Signal to Interference plus Noise Ratio) interval and the spatial correlation interval is determined.
  • the MMSE algorithm module 12 calculates an SINR (Signal to Interference plus Noise Ratio) value of the independent signal, and obtains an MCS value of the independent signal by querying a correspondence table between the SINR and the MCS, specifically: calculating a channel estimation value, according to the channel estimation value. Calculating the SINR (Signal to Interference plus Noise Ratio) value of the independent signal under the MMSE algorithm, and querying the SINR and MCS correspondence table according to the SINR (Signal to Interference plus Noise Ratio) value of the independent signal, The MCS value of the independent signal under the corresponding MMSE algorithm.
  • the spatial correlation estimation module 13 calculates the spatial correlation by specifically calculating a determinant value of the spatial channel according to the channel estimation value, and determining a spatial correlation according to the determinant value of the spatial channel.
  • the adjustment amount calculation module 14 obtains the MCS adjustment amount of the SD algorithm by querying the SD algorithm MCS adjustment scale according to the SINR (Signal to Interference plus Noise Ratio) value and spatial correlation of the independent signal, specifically: SINR according to the independent signal ( Signal and interference plus noise ratio) and spatial correlation, query the SD algorithm MCS adjustment scale, find the SINR (signal to interference plus noise ratio) value of the independent signal and the MCS adjustment of the SD algorithm uniquely determined by the spatial correlation.
  • SINR Signal to Interference plus Noise Ratio
  • the adjustment amount calculation module 14 calculates the MCS value of the SD algorithm according to the MCS value of the independent signal and the MCS adjustment amount of the SD algorithm, and specifically: the MCS value of the independent signal of the MMSE algorithm and the MCS adjustment amount of the SD algorithm Add, get the MCS value under the SD algorithm.
  • FIG. 2 is a schematic flowchart of a method for implementing an MCS for a MIMO SD receiver according to an embodiment of the present invention. As shown in FIG. 2, the method includes The following steps:
  • Step 201 Configure a correspondence table between the SINR and the MCS and an SDS adjustment table of the SD algorithm. Specifically, configure a correspondence table between the SINR and the MCS and an SDS adjustment table of the SD algorithm in the MIMO SD receiver, where the correspondence table between the SINR and the MCS The content is the mapping relationship between the MCS value of each independent signal and the corresponding SINR (Signal to Interference plus Noise Ratio) value of each independent signal under the MMSE algorithm; the SD algorithm MCS adjustment scale is a two-dimensional table, spatial correlation and The SINR is divided into three sections: low, medium, and high.
  • SINR Signal to Interference plus Noise Ratio
  • Each row in the SD algorithm MCS adjustment scale corresponds to the SINR (signal to interference plus noise ratio) interval
  • each column of the SD algorithm MCS adjustment scale corresponds to the spatial correlation interval, according to one SINR (Signal to Interference plus Noise Ratio) interval and a spatial correlation interval, which can determine the MCS adjustment of the SD algorithm of the SINR (Signal to Interference plus Noise Ratio) interval and the spatial correlation interval
  • Storage module of the MIMO SD receiver A correspondence table and an SD algorithm MCS adjustment amount table for storing the SINR and the MCS.
  • Step 202 Calculate the SINR value of the independent signal, and query the pair of SINR and MCS.
  • the MCS value of the independent signal should be obtained;
  • the channel estimation module of the MIMO SD receiver calculates and outputs a channel estimation value
  • the MMSE algorithm module of the MIMO SD receiver calculates the SINR (Signal to Interference plus Noise Ratio) of the independent signal of the MMSE algorithm according to the channel estimation value.
  • the MMSE algorithm module queries the configured SINR and MCS correspondence table according to the SINR (Signal to Interference plus Noise Ratio) value of the independent signal, and obtains the SINR (Signal to Interference plus Noise Ratio) value of the independent signal.
  • the MCS value of the independent signal of the MMSE algorithm The MCS value of the independent signal of the MMSE algorithm.
  • Step 203 calculating spatial correlation
  • the spatial correlation estimation module of the MIMO SD receiver calculates the determinant value of the spatial channel, and the determinant value of the spatial channel can reflect the spatial correlation of the channel, and thus according to the spatial channel The determinant value determines the spatial correlation.
  • Step 204 Query the SD algorithm MCS adjustment scale according to the SINR value and the spatial correlation of the independent signal, and obtain the MCS adjustment amount of the SD algorithm.
  • the adjustment amount calculation module of the MIMO SD receiver queries the SD algorithm MCS adjustment scale, and adjusts The quantity calculation module finds the SINR (Signal to Interference plus Noise Ratio) value of the independent signal and the MCS adjustment amount of the SD algorithm uniquely determined by the spatial correlation in the SD algorithm MCS adjustment scale.
  • Step 205 Calculate an MCS value in the SD algorithm according to an MCS value of the independent signal and an MCS adjustment amount of the SD algorithm.
  • the adjustment calculation module of the MIMO SD receiver adds the MCS value of the independent signal of the MMSE algorithm to the MCS adjustment of the SD algorithm to obtain the MCS value of the SD algorithm.
  • This embodiment takes the selection of a CQI (Channel Quality Indicator) value in LTE as an example, where LTE
  • the protocol specifies 15 CQIs (Channel Quality Indicators), and each CQI (Channel Quality Indicator) value corresponds to an MCS.
  • the method includes the following steps:
  • Step 1 Configure a correspondence table between the SINR and the MCS and an SD algorithm CQI (Channel Quality Indicator) adjustment scale;
  • the SINR and MCS correspondence table and the SD algorithm CQI (Channel Quality Indicator) adjustment amount table are configured in the MIMO SD receiver; wherein, under various fading channels and Gaussian channel environments, according to the MMSE demodulation algorithm, The minimum SINR (Signal to Interference plus Noise Ratio) value corresponding to the CQI (Channel Quality Indicator) respectively determines a correspondence table between the SINR and the MCS under the MMSE algorithm; the storage module of the MIMO SD receiver is used to store the SINR and the MCS Correspondence table and SD algorithm CQI (channel quality indicator) adjustment scale;
  • CQI channel quality indicator
  • SD algorithm CQI channel quality indicator
  • SINR signal to interference plus noise ratio
  • Step 2 Calculate the SINR value of the independent signal, and query the correspondence table between the SINR and the MCS to obtain the MCS value of the independent signal.
  • the channel estimation module of the MIMO SD receiver outputs the channel estimation value on each subcarrier.
  • the channel transmission matrix Hn on each subcarrier is set, where the dimension is the number of receiving antennas multiplied by the transmission antenna.
  • the MMSE algorithm module of the MIMO SD receiver calculates the SINR of the independent signal of the MMSE algorithm according to the channel estimation value output by the channel estimation module. (Signal to interference plus noise ratio) value, the MMSE algorithm module queries in the correspondence table of SINR and MCS to obtain the CQI (Channel Quality Indicator) value of the independent signal under the MMSE algorithm.
  • SINR Signal to interference plus noise ratio
  • Step 3 calculate spatial correlation
  • N the total number of subcarriers used to calculate spatial channel correlation.
  • all subcarriers on one OFDM symbol or all subcarriers on a reference signal position on one OFDM symbol may be taken, and ⁇ ⁇ ⁇ is space on N subcarriers.
  • the accumulated value of the determinant value of the channel may be taken, and ⁇ ⁇ ⁇ is space on N subcarriers.
  • Step 4 Query the SD algorithm MCS adjustment scale according to the SINR value and the spatial correlation of the independent signal, and obtain the CQI (channel quality indicator) adjustment amount of the SD algorithm;
  • the adjustment amount calculation module queries the SD algorithm MCS adjustment scale to find the respective intervals of SINR (signal to interference plus noise ratio) values and spatial correlation.
  • the adjustment amount calculation module finds the SINR (Signal to Interference plus Noise Ratio) value of the independent signal and the CQI (Channel Quality Indicator) adjustment amount of the SD algorithm uniquely determined by the spatial correlation in the SD algorithm MCS adjustment scale.
  • Step 5 Calculate a CQI (Channel Quality Indicator) value under the SD algorithm according to the MCS value of the independent signal and the CQI (Channel Quality Indicator) adjustment amount of the SD algorithm;
  • the adjustment amount calculation module adds the MCS value of the independent signal of the MMSE algorithm to the CQI (channel quality indicator) adjustment amount of the SD algorithm to obtain a CQI (channel quality indicator) value under the SD algorithm.

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Abstract

本发明实施例公开一种MIMO SD接收机及其选择MCS的方法,该MIMO SD接收机包括:存储模块配置SINR与MCS的对应表和SD算法MCS调整量表;MMSE算法模块计算独立信号的SINR值,并通过查询SINR与MCS的对应表得到该独立信号的MCS值;空间相关性估计模块计算空间相关性,调整量计算模块根据独立信号的SINR值和空间相关性,通过查询SD算法MCS调整量表得到SD算法的MCS调整量;根据独立信号的MCS值和SD算法的MCS调整量,计算SD算法下的MCS值。根据本发明实施例的技术方案,MIMO SD接收机能够准确的选出MCS值,提高系统的容量和信道的可靠性。

Description

一种 MIMO SD接收机及其选择 MCS的方法 技术领域
本发明实施例涉及无线通信系统,特别涉及一种 MIMO SD接收机及其 选择 MCS的方法。 背景技术
典型的无线信道是随机变化的, 具有频率选择性和时变性的特点。 在 无线通信系统的设计中, 这种无线信道的随机性需要考虑在内, 而更加优 越的设计是可以利用这种随机性来提高无线通信系统的性能和容量。 其中 一种重要的思想是根据信道的即时质量, 通过对调制和编码方式(MCS, Modulation and Coding Scheme ) 的动态选择来改变传输速率, MCS的动态 选择技术是 3G、 4G乃至未来宽带无线通信的关键技术, 在 LTE、 WiMAX 等领域得到广泛应用; MCS的动态选择技术要求传输机有信道的即时质量 的信息, 即时质量的信息可以通过接收机的反馈得到。 在实际的应用中, 出于减少反馈开销的考虑, 接收机会通过信道估计选择 MCS, 并将选择的 MCS反馈给传输机使用。
在无线通信系统中采用多入多出 (MIMO , Multiple Input Multiple Output )技术可以有效提高系统的容量和无线信道的可靠性。特别是当采用 空分复用方式传输时, 可以传输多路独立信号, 因而获得明显的信道容量 增益。 独立信号的最大数目等于传输天线数和接收天线数中较小的数。 多 路独立信号经过信道后, 在接收机相互干扰, 每一路独立信号的接收性能 取决于信号功率和噪声功率 (包括干扰功率) 的比值, 独立信号之间的相 互干扰对每一路独立信号的信道质量指示符 (CQI , Channel Quality Indicator )选择提出了挑战。 接收机的算法可以分为线性算法和非线性算法, 线性算法中, 最小均 方误差 (MMSE, Minimum Mean Squared Error )算法因其实现复杂度低而 被广泛采用, 当采用 MMSE算法时, 每一路独立信号的信号与干扰加噪声 比( SINR, Signal to Interference plus Noise Ratio )可以计算得到, 因此 MCS 的选择相对直接。 在非线性算法中, 球形译码(SD, Sphere Decoding ) 算 法实现了最理想的最大似然(ML, Maximal Likelihood )算法, 而且实现复 杂度相对其他的 ML算法而言较低; 和线性算法相比, SD在信道高空间相 关性和 /或高传输码率的条件下的性能优越 ί艮多。 因此 SD算法对系统实现 最优的设计具有关键的作用,但是当接收机采用 SD算法时,每一路独立信 号的接收性能无法通过直接的计算得到, 因而 MCS的动态选择更加困难。 发明内容
有鉴于此,本发明实施例的主要目的在于提供一种 MIMO SD接收机及 其选择 MCS的方法, MIMO SD接收机能够准确的选出 MCS值,从而提高 系统的容量和信道的可靠性。
为达到上述目的, 本发明实施例的技术方案是这样实现的:
本发明提供一种 MIMO SD接收机, 包括: 存储模块、 MMSE算法模 块、 空间相关性估计模块、 调整量计算模块; 其中,
存储模块,用于保存配置的 SINR与 MCS的对应表和 SD算法 MCS调 整量表;
MMSE算法模块, 用于计算独立信号的 SINR值, 并通过查询 SINR与
MCS的对应表得到该独立信号的 MCS值;
空间相关性估计模块, 用于计算空间相关性;
调整量计算模块, 用于根据独立信号的 SINR值和空间相关性,通过查 询 SD算法 MCS调整量表得到 SD算法的 MCS调整量;还用于,根据独立 信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值。 上述装置中,所述 SINR与 MCS的对应表为 MMSE算法下每路独立信 号 MCS值与对应的每路独立信号的 SINR值的映射关系;
所述 SD算法 MCS调整量表中每行对应 SINR区间, 每列对应空间相 关性区间, ^^据一个 SINR区间和一个空间相关性区间, 确定该 SINR区间 和空间相关性区间的 SD算法的 MCS调整量。
上述装置中, 所述 MMSE算法模块具体用于: 计算信道估计值, 根据 该信道估计值计算 MMSE算法下该路独立信号的 SINR值, 并根据该独立 信号的 SINR值,在所述 SINR与 MCS的对应表中查询,得到对应的 MMSE 算法下该路独立信号的 MCS值。
上述装置中, 所述空间相关性估计模块具体用于: 根据信道估计值, 计算空间信道的行列式值, 根据空间信道的行列式值确定空间相关性。
上述装置中, 所述调整量计算模块具体用于:
根据独立信号的 SINR值和空间相关性, MIMO SD接收机查询 SD算 法 MCS调整量表,找到该独立信号的 SINR值和空间相关性唯一确定的 SD 算法的 MCS调整量; 将 MMSE算法下该路独立信号的 MCS值与 SD算法 的 MCS调整量相加, 得到 SD算法下的 MCS值。
本发明还提供一种 MIMO SD接收机选择 MCS的方法, 包括: 配置 SINR与 MCS的对应表和 SD算法 MCS调整量表;
计算独立信号的 SINR值, 并通过查询 SINR与 MCS的对应表得到该 独立信号的 MCS值;
计算空间相关性, 根据独立信号的 SINR值和空间相关性, 通过查询
SD算法 MCS调整量表得到 SD算法的 MCS调整量;
根据独立信号的 MCS值和 SD算法的 MCS调整量,计算 SD算法下的
MCS值。
上述方法中,所述 SINR与 MCS的对应表为 MMSE算法下每路独立信 号 MCS值与对应的每路独立信号的 SINR值的映射关系;
所述 SD算法 MCS调整量表中每行对应 SINR区间, 每列对应空间相 关性区间, ^^据一个 SINR区间和一个空间相关性区间, 确定该 SINR区间 和空间相关性区间的 SD算法的 MCS调整量。
上述方法中,所述计算独立信号的 SINR值,并通过查询 SINR与 MCS 的对应表得到该独立信号的 MCS值为:
MIMO SD接收机计算信道估计值, 根据该信道估计值计算 MMSE算 法下该路独立信号的 SINR值,并根据该独立信号的 SINR值,在所述 SINR 与 MCS的对应表中查询, 得到对应的 MMSE算法下该路独立信号的 MCS 值。
上述方法中, 所述计算空间相关性为:
MIMO SD接收机根据信道估计值, 计算空间信道的行列式值, 根据空 间信道的行列式值确定空间相关性。
上述方法中, 所述根据空间信道的行列式值确定空间相关性为: 空间相关性等于∑IHnl/N,其中 Ν为用于计算空间信道相关性的子载波 总个数, Σ ΙΗηΙ为 Ν个子载波上空间信道的行列式值的累加值, Ηη为每个 子载波上的信道传输矩阵。
上述方法中, 所述根据独立信号的 SINR值和空间相关性, 通过查询 SD算法 MCS调整量表得到 SD算法的 MCS调整量为:
根据独立信号的 SINR值和空间相关性, MIMO SD接收机查询 SD算 法 MCS调整量表,找到该独立信号的 SINR值和空间相关性唯一确定的 SD 算法的 MCS调整量。
上述方法中, 所述根据独立信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值为:
MIMO SD接收机将 MMSE算法下该路独立信号的 MCS值与 SD算法 的 MCS调整量相加, 得到 SD算法下的 MCS值。
本发明实施例提供的 MIMO SD接收机及其选择 MCS 的方法, 配置 SINR与 MCS的对应表和 SD算法 MCS调整量表; 计算独立信号的 SINR (信号与干扰加噪声比)值, 并通过查询 SINR与 MCS的对应表得到该独 立信号的 MCS值; 计算空间相关性, 根据独立信号的 SINR (信号与干扰 加噪声比 )值和空间相关性, 通过查询 SD算法 MCS调整量表得到 SD算 法的 MCS调整量; 根据独立信号的 MCS值和 SD算法的 MCS调整量, 计 算 SD算法下的 MCS值, 因此本发明实施例中, 根据信道的空间相关性和 SINR (信号与干扰加噪声比)值, 对 MIMO MMSE接收机的 MCS值进行 选择, 以得到 MIMO SD接收机的 MCS值, 即 MIMO SD接收机能够准确 的选出 MCS值, 从而提高系统的容量和信道的可靠性; 此外, 本发明实施 例中的计算方法实现简单, 具有较高可行性。 附图说明
图 1是本发明实施例实现 MIMO SD接收机的结构示意图;
图 2是本发明实施例实现 MIMO SD接收机选择 MCS的方法的流程示 意图。 具体实施方式
本发明实施例的基本思想是: 存储模块保存配置 SINR与 MCS的对应 表和 SD算法 MCS调整量表; MMSE算法模块计算独立信号的 SINR (信 号与干扰加噪声比)值, 并通过查询 SINR与 MCS的对应表得到该独立信 号的 MCS值; 空间相关性估计模计算空间相关性, 调整量计算模块根据独 立信号的 SINR (信号与干扰加噪声比 )值和空间相关性, 通过查询 SD算 法 MCS调整量表得到 SD算法的 MCS调整量;根据独立信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值。 下面通过附图及具体实施例对本发明实施例再做进一步的详细说明。 本发明实施例提供一种 MIMO SD接收机, 图 1是本发明实施例实现 MIMO SD接收机的结构示意图, 如图 1所示, 该装置包括: 存储模块 11、 MMSE算法模块 12、 空间相关性估计模块 13、 调整量计算模块 14; 其中, 存储模块 11 ,用于保存配置的 SINR与 MCS的对应表和 SD算法 MCS 调整量表;
MMSE算法模块 12, 用于计算独立信号的 SINR (信号与干扰加噪声 比 )值, 并通过查询 SINR与 MCS的对应表得到该独立信号的 MCS值; 空间相关性估计模块 13, 用于计算空间相关性;
调整量计算模块 14,用于根据独立信号的 SINR(信号与干扰加噪声比 ) 值和空间相关性,通过查询 SD算法 MCS调整量表得到 SD算法的 MCS调 整量; 还用于, 根据独立信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值。
所述 SINR与 MCS的对应表为 MMSE算法下每路独立信号 MCS值与 对应的每路独立信号的 SINR (信号与干扰加噪声比)值的映射关系。
所述 SD算法 MCS调整量表中每行对应 SINR (信号与干扰加噪声比 ) 区间, 每列对应空间相关性区间, 根据一个 SINR (信号与干扰加噪声比) 区间和一个空间相关性区间, 确定该 SINR (信号与干扰加噪声比) 区间和 空间相关性区间的 SD算法的 MCS调整量。
所述 MMSE算法模块 12计算独立信号的 SINR (信号与干扰加噪声比 ) 值, 并通过查询 SINR与 MCS的对应表得到该独立信号的 MCS值具体为: 计算信道估计值, 根据该信道估计值计算 MMSE 算法下该路独立信号的 SINR (信号与干扰加噪声比 )值, 并根据该独立信号的 SINR (信号与干扰 加噪声比)值, 在所述 SINR与 MCS的对应表中查询, 得到对应的 MMSE 算法下该路独立信号的 MCS值。 所述空间相关性估计模块 13计算空间相关性具体为:根据信道估计值, 计算空间信道的行列式值, 根据空间信道的行列式值确定空间相关性。
所述调整量计算模块 14根据独立信号的 SINR (信号与干扰加噪声比 ) 值和空间相关性,通过查询 SD算法 MCS调整量表得到 SD算法的 MCS调 整量具体为: 根据独立信号的 SINR (信号与干扰加噪声比 )值和空间相关 性, 查询 SD算法 MCS调整量表, 找到该独立信号的 SINR (信号与干扰 加噪声比 )值和空间相关性唯一确定的 SD算法的 MCS调整量。
所述调整量计算模块 14根据独立信号的 MCS值和 SD算法的 MCS调 整量,计算 SD算法下的 MCS值具体为: 将 MMSE算法下该路独立信号的 MCS值与 SD算法的 MCS调整量相加, 得到 SD算法下的 MCS值。
基于上述装置, 本发明实施例还提供一种 MIMO SD接收机选择 MCS 的方法, 图 2是本发明实施例实现 MIMO SD接收机选择 MCS的方法的流 程示意图, 如图 2所示, 该方法包括以下步驟:
步驟 201 , 配置 SINR与 MCS的对应表和 SD算法 MCS调整量表; 具体的 , 在 MIMO SD接收机中配置 SINR与 MCS的对应表和 SD算 法 MCS调整量表, 其中, SINR与 MCS的对应表的内容是 MMSE算法下 每路独立信号 MCS值与对应的每路独立信号的 SINR (信号与干扰加噪声 比)值的映射关系; SD算法 MCS调整量表是一个二维表, 空间相关性和 SINR分别分成低、 中、 高三个区间, SD算法 MCS调整量表中的每行对应 SINR (信号与干扰加噪声比) 区间, SD算法 MCS调整量表的每列对应空 间相关性区间, 根据一个 SINR (信号与干扰加噪声比) 区间和一个空间相 关性区间, 能够确定该 SINR (信号与干扰加噪声比) 区间和空间相关性区 间的 SD算法的 MCS调整量; MIMO SD接收机的存储模块用于存储所述 SINR与 MCS的对应表和 SD算法 MCS调整量表。
步驟 202, 计算独立信号的 SINR值, 并通过查询 SINR与 MCS的对 应表得到该独立信号的 MCS值;
具体的, MIMO SD接收机的信道估计模块计算并输出信道估计值, MIMO SD接收机的 MMSE算法模块根据该信道估计值, 计算 MMSE算法 下该路独立信号的 SINR (信号与干扰加噪声比 )值, MMSE算法模块根据 该独立信号的 SINR (信号与干扰加噪声比)值, 在配置的 SINR与 MCS 的对应表中进行查询, 得到该独立信号的 SINR (信号与干扰加噪声比)值 对应的 MMSE算法下该路独立信号的 MCS值。
步驟 203, 计算空间相关性;
具体的, 根据信道估计模块输出的信道估计值, MIMO SD接收机的空 间相关性估计模块计算空间信道的行列式值, 空间信道的行列式值能够反 映信道的空间相关性, 因此根据空间信道的行列式值可以确定空间相关性。
步驟 204, 根据独立信号的 SINR值和空间相关性, 查询 SD算法 MCS 调整量表, 得到 SD算法的 MCS调整量;
具体的, 根据步驟 202中得到的独立信号的 SINR (信号与干扰加噪声 比)值和步驟 203中得到的空间相关性, MIMO SD接收机的调整量计算模 块查询 SD算法 MCS调整量表,调整量计算模块在 SD算法 MCS调整量表 中找到该独立信号的 SINR (信号与干扰加噪声比 )值和空间相关性唯一确 定的 SD算法的 MCS调整量。
步驟 205, 根据独立信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值;
具体的, MIMO SD接收机的调整量计算模块将 MMSE算法下该路独 立信号的 MCS值与 SD算法的 MCS调整量相加, 得到 SD算法下的 MCS 值。
实施例一
本实施例以 LTE中 CQI (信道质量指示符)值的选择为例, 其中, LTE 协议中规定了 15种 CQI (信道质量指示符), 每种 CQI (信道质量指示符) 值对应一个 MCS, 该方法包括以下步驟:
步驟 1 ,配置 SINR与 MCS的对应表和 SD算法 CQI(信道质量指示符 ) 调整量表;
具体的 , 在 MIMO SD接收机中配置 SINR与 MCS的对应表和 SD算 法 CQI (信道质量指示符)调整量表; 其中, 仿真各种衰落信道和高斯信 道环境下, 根据 MMSE解调算法下 15种 CQI (信道质量指示符)分别对 应的最低 SINR (信号与干扰加噪声比 )值, 确定 MMSE算法下 SINR与 MCS的对应表; MIMO SD接收机的存储模块用于存储所述 SINR与 MCS 的对应表和 SD算法 CQI (信道质量指示符 )调整量表;
根据仿真不同信道环境和信道相关性条件下, 15种 CQI (信道质量指 示符) 的 MMSE算法和 SD算法的性能差异, 确定 SD算法相对 MMSE算 法的在不同 SINR (信号与干扰加噪声比)值下的 CQI (信道质量指示符) 调整量; SD算法 CQI (信道质量指示符)调整量表是一个二维表, 空间相 关性和 SINR (信号与干扰加噪声比)值分别分成低、 中、 高三个区间, 每 行对应一个 SINR (信号与干扰加噪声比) 区间, 每列对应一个空间相关性 区间, 根据一个 SINR (信号与干扰加噪声比) 区间和一个空间相关性区间 能够确定, 该 SINR (信号与干扰加噪声比) 区间和空间相关性区间的 CQI (信道质量指示符)调整量。
步驟 2, 计算独立信号的 SINR值, 并查询 SINR与 MCS的对应关系 表, 得到该独立信号的 MCS值;
具体的, MIMO SD接收机的信道估计模块输出为每个子载波上的信道 估计值, 本实施例中, 设每个子载波上的信道传输矩阵 Hn, 其中的维数为 接收天线数乘以传输天线数, MIMO SD接收机的 MMSE算法模块根据信 道估计模块输出的信道估计值, 计算 MMSE算法下该路独立信号的 SINR (信号与干扰加噪声比)值, MMSE算法模块在 SINR与 MCS的对应表中 进行查询, 得到在 MMSE算法下该路独立信号的 CQI (信道质量指示符 ) 值。
步驟 3, 计算空间相关性;
具体的, MIMO SD接收机的空间相关性估计模块根据信道估计值计算 空间信道的行列式值, 空间信道的行列式值反映了信道的空间相关性, 即 空间相关性 =∑ IHnl/N,其中 N为用于计算空间信道相关性的子载波总个数, 通常可以取一个 OFDM符号上的所有子载波或一个 OFDM符号上的参考信 号位置上的所有子载波, Σ ΙΗηΙ为 N个子载波上空间信道的行列式值的累加 值。
步驟 4, 根据独立信号的 SINR值和空间相关性, 查询 SD算法 MCS 调整量表, 得到 SD算法的 CQI (信道质量指示符 )调整量;
具体的, 根据 SINR (信号与干扰加噪声比)值和空间相关性, 调整量 计算模块查询 SD算法 MCS调整量表, 找到 SINR (信号与干扰加噪声比 ) 值和空间相关性所在的各自区间, 调整量计算模块在 SD算法 MCS调整量 表中找到该独立信号的 SINR (信号与干扰加噪声比)值和空间相关性唯一 确定的 SD算法的 CQI (信道质量指示符 )调整量。
步驟 5, 根据独立信号的 MCS值和 SD算法的 CQI (信道质量指示符 ) 调整量, 计算得到 SD算法下的 CQI (信道质量指示符 )值;
具体的, 调整量计算模块将 MMSE算法下该路独立信号的 MCS值与 SD算法的 CQI (信道质量指示符 )调整量相加,得到 SD算法下的 CQI (信 道质量指示符 )值。
以上所述, 仅为本发明实施例的较佳实施例而已, 并非用于限定本发 明实施例的保护范围, 凡在本发明实施例的精神和原则之内所作的任何修 改、 等同替换和改进等, 均应包含在本发明实施例的保护范围之内。

Claims

权利要求书
1、一种 MIMO SD接收机,其特征在于,该装置包括:存储模块、 MMSE 算法模块、 空间相关性估计模块、 调整量计算模块; 其中,
存储模块,用于保存配置的 SINR与 MCS的对应表和 SD算法 MCS调 整量表;
MMSE算法模块, 用于计算独立信号的 SINR值, 并通过查询 SINR与 MCS的对应表得到该独立信号的 MCS值;
空间相关性估计模块, 用于计算空间相关性;
调整量计算模块, 用于根据独立信号的 SINR值和空间相关性, 通过查 询 SD算法 MCS调整量表得到 SD算法的 MCS调整量; 还用于,根据独立 信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值。
2、根据权利要求 1所述的装置, 其特征在于, 所述 SINR与 MCS的对 应表为 MMSE算法下每路独立信号 MCS值与对应的每路独立信号的 SINR 值的映射关系;
所述 SD算法 MCS调整量表中每行对应 SINR区间, 每列对应空间相 关性区间, ^^据一个 SINR区间和一个空间相关性区间, 确定该 SINR区间 和空间相关性区间的 SD算法的 MCS调整量。
3、 根据权利要求 1所述的装置, 其特征在于, 所述 MMSE算法模块 具体用于: 计算信道估计值, 根据该信道估计值计算 MMSE算法下该路独 立信号的 SINR值, 并根据该独立信号的 SINR值, 在所述 SINR与 MCS 的对应表中查询, 得到对应的 MMSE算法下该路独立信号的 MCS值。
4、 根据权利要求 1所述的装置, 其特征在于, 所述空间相关性估计模 块具体用于: 根据信道估计值, 计算空间信道的行列式值, 根据空间信道 的行列式值确定空间相关性。
5、 根据权利要求 1所述的装置, 其特征在于, 所述调整量计算模块具 体用于:
根据独立信号的 SINR值和空间相关性, MIMO SD接收机查询 SD算 法 MCS调整量表,找到该独立信号的 SINR值和空间相关性唯一确定的 SD 算法的 MCS调整量; 将 MMSE算法下该路独立信号的 MCS值与 SD算法 的 MCS调整量相加, 得到 SD算法下的 MCS值。
6、 一种 MIMO SD接收机选择 MCS的方法, 其特征在于, 该方法包 括:
配置 SINR与 MCS的对应表和 SD算法 MCS调整量表;
计算独立信号的 SINR值, 并通过查询 SINR与 MCS的对应表得到该 独立信号的 MCS值;
计算空间相关性, 根据独立信号的 SINR值和空间相关性, 通过查询 SD算法 MCS调整量表得到 SD算法的 MCS调整量;
根据独立信号的 MCS值和 SD算法的 MCS调整量,计算 SD算法下的 MCS值。
7、根据权利要求 6所述的方法, 其特征在于, 所述 SINR与 MCS的对 应表为 MMSE算法下每路独立信号 MCS值与对应的每路独立信号的 SINR 值的映射关系;
所述 SD算法 MCS调整量表中每行对应 SINR区间, 每列对应空间相 关性区间, ^^据一个 SINR区间和一个空间相关性区间, 确定该 SINR区间 和空间相关性区间的 SD算法的 MCS调整量。
8、根据权利要求 6所述的方法,其特征在于,所述计算独立信号的 SINR 值, 并通过查询 SINR与 MCS的对应表得到该独立信号的 MCS值为:
MIMO SD接收机计算信道估计值, 根据该信道估计值计算 MMSE算 法下该路独立信号的 SINR值,并根据该独立信号的 SINR值,在所述 SINR 与 MCS的对应表中查询, 得到对应的 MMSE算法下该路独立信号的 MCS 值。
9、根据权利要求 6所述的方法, 其特征在于, 所述计算空间相关性为: MIMO SD接收机根据信道估计值, 计算空间信道的行列式值, 根据空 间信道的行列式值确定空间相关性。
10、 根据权利要求 9所述的方法, 其特征在于, 所述根据空间信道的 行列式值确定空间相关性为:
空间相关性等于∑ IHnl/N,其中 N为用于计算空间信道相关性的子载波 总个数, Σ ΙΗηΙ为 N个子载波上空间信道的行列式值的累加值, Ηη为每个 子载波上的信道传输矩阵。
11、 根据权利要求 6所述的方法, 其特征在于, 所述根据独立信号的
SINR值和空间相关性, 通过查询 SD算法 MCS调整量表得到 SD算法的
MCS调整量为:
根据独立信号的 SINR值和空间相关性, MIMO SD接收机查询 SD算 法 MCS调整量表,找到该独立信号的 SINR值和空间相关性唯一确定的 SD 算法的 MCS调整量。
12、 根据权利要求 6所述的方法, 其特征在于, 所述根据独立信号的 MCS值和 SD算法的 MCS调整量, 计算 SD算法下的 MCS值为:
MIMO SD接收机将 MMSE算法下该路独立信号的 MCS值与 SD算法 的 MCS调整量相加, 得到 SD算法下的 MCS值。
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Citations (3)

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Publication number Priority date Publication date Assignee Title
CN101375523A (zh) * 2005-01-12 2009-02-25 美商亚瑟罗斯通讯股份有限公司 在mimo系统中选择mcs
CN101388703A (zh) * 2008-10-08 2009-03-18 北京创毅视讯科技有限公司 一种多用户mimo预编码的方法及系统
CN101465717A (zh) * 2007-12-20 2009-06-24 索尼株式会社 量化的预编码的空间复用mimo用的改进式选择准则

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101375523A (zh) * 2005-01-12 2009-02-25 美商亚瑟罗斯通讯股份有限公司 在mimo系统中选择mcs
CN101465717A (zh) * 2007-12-20 2009-06-24 索尼株式会社 量化的预编码的空间复用mimo用的改进式选择准则
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