搜索资源列表
VBLASTdetectors
- 一种常用空分复用的MIMO系统,v-blast系统的各种检测算法:ML,MMSE,ZF,以及采用迫零的连续干扰消除检测算法
ML_equalizer_for_STBC_systems
- 基于STBC的ML检测MIMO仿真,可以完成ML联合STBC仿真。-The ML detection of MIMO STBC-based simulation, simulation can be completed ML joint STBC.
HW3P1
- code to test the mimo system for the ML and MZ
W5
- code to test the mimo system for the ML and MZ
icdtool
- code to test the mimo system for the ML and MZ
MP_DOA
- 针对多径效应的影响,提出了一种基于矩阵束的MIMO 雷达低仰角快速估计方法。该方法同时考虑了发射多径信号和接收多径信号,采用单样本数信号矢量构造了一个前后向矩阵束,并利用两个酉矩阵对该矩阵束进行降维处理,最后采用广义特征值分解的总体最小二乘法来估计目标角度。算法不需要估计数据协方差矩阵,可在低 信噪比和单样本数情况下,有效地克服多径效应,实现同时多目标低仰角估计,相比最大似然算法,避免了谱峰搜索,计算量小。仿真结果验证了该算法的有效性。-To overcome the multipath e
MIMO_detection
- MIMO系统的几种检测方案,ZF,MMSE,ML译码,其中前两种可以运行,后者有些问题。代码均以调通-Several detection scheme for MIMO systems , ZF , MMSE, the ML decoding , the first two can run,there are some problems of the latter . all Code can run rightly
EJSR_59_4_08
- Bit Error Rate Performance Analysis of ZF, ML and MMSE Equalizers for MIMO Wireless Communication Receiver
ML_Equalizer_2X2
- ML Receiver for 2x2 MIMO
2moreqamcodes
- the code is about ML detector of mimo technology ,,,,we need of vhdl code for all detectors
MIMO_detection
- MIMO 系统中 信号检测算法的比较 zf mmse ML-Performance of zero-forcing detectors over MIMO flat-correlated Ricean fading channels
ML_VP
- 基于穷搜算法的向量扰动预编码脚本,用于测试该算法的误比特率性能。系统模型为4×4的MIMO系统。调制方式为4QAM。参数可以更改。-vector perturbation(VP) precoding algorithm based on exhaustive search (ML). 4*4 MIMO system with 4QAM.
5-files
- It contains 4 matlab codes for ZF,MMSE,ML equalizer for MIMO systems and 1 document based on linear detector for MIMO system
mimo_ML_detection
- MIMO ML detection Rayleigh channel 採用16QAM-MIMO ML detection Rayleigh channel using 16QAM
PIC_SDR_LIANG
- 基于窄带mimo系统的最大似然检测算法,基于窄带mimo系统的最大似然检测算法-ML detection
QPSK-ALL
- 简单的MIMO模拟 假定QPSK,ML解码(SM ZF检测器除外)。 mrc.m - 最大比例组合 stc.m - 具有1和2个接收天线的Alamouti空时分组码 bf.m - 特征波束形成 sm.m - 空间复用2x2(ML解码和次优逼迫) 简单的OFDM仿真 模拟保护带,用于信道估计的循环前缀前导码符号(Simple MIMO simulations Assumes QPSK, ML decoding (except SM ZF detector).
多用户检测
- 主要实现了接收天线数量和发送天线数量可配的mimo系统多用户检测,分别采用ML,MMSE,ZF检测方法,得到性能比较曲线。(The multi-user detection of mimo system with the number of receiving antennas and the number of transmitting antennas is mainly realized. The performance comparison curve is obtained by us
MMMO
- MIMO 2 3系统ML和ZF检测的BER性能仿真(BER performance Simulation of ML and ZF Detection in MIMO 23 system)
大规模MIMO__detector
- 实现MIMO基本框架,并利用经典ZF ML算法进行检测,含图(Realize the basic framework of MIMO, and use the classical ZF ML algorithm to detect, including graphs)
03-2x2MIMO系统的完整数据链仿真
- % Type of different detectors, parameters for Detector.m ML = 1; % Joint ML Detector JMMSE = 2; % Joint MMSE Detector ZF = 3; % Joint Zero-Forcing Detector % Type of different antenna selection criteria methods MBER = 1; MMI = 2; LAZY = 3; MNP = 4