搜索资源列表
ofdm_sim
- OFDM系统中ZF均衡和MMSE均衡算法源码-OFDM system ZF equalization and MMSE equalization algorithm source code
MIMO23_ML_ZF
- MIMO 2*3系统ML和ZF检测的BER性能仿真-MIMO 2* 3 System ML and ZF detection BER performance simulation
LTE_channel_estimator
- LTE规范 信道估计 MMSE zf -channel estimator lte
LTE_channel_estimat2
- LTE规范 信道估计 MMSE zf -channel estimator lte
blast
- 仿真原型程序,仿真四种（ZF,ZF-SIC,MMSE,MMSE-SIC） Vblast接收机的检测性能，绘制误比特率～信噪比曲线-zf mmse vblast
V-BLAST-[matlab-source-code]
- 本程序是对V-BLAST系统及其检测算法的仿真，可采用BPSK,QPSK,16QAM,64QAM调制。检测算法为ML，MMSE,ZF,以及采用迫零的连续干扰消除检测算法。-This program is a simulation, the V-BLAST system and its detection algorithm can be used for BPSK, QPSK, 16QAM, 64QAM modulation. Detection algorithm for the ML, M
ZF
- Matlab code for MIMO Zero Forcing
zf_mmse
- code matlab for computing BER comparison MIMO 2x2 of ZF equalizer and MMSE equalizer (Rayleigh channel)
MIMO
- 在matlab的环境下，实现MIMO检测功能，包括最大似然检测（ML），最小均方误差（MMSE）检测和迫零（ZF）检测-In the matlab environment, to achieve MIMO detection, including maximum likelihood detection (ML), minimum mean square error (MMSE) detection and zero-forcing (ZF) detection
singleusermimo
- ZF、MMSE、ZF.SIC、 MMSE—SIC这4种算法的性能优劣,并用Matlab进行仿真,分析了这些算法的性能.结果表明,性 能最好的为MMSE—SIC,这是zf-ZF, MMSE, ZF.SIC, MMSE-SIC these four algorithms performance advantages and disadvantages, and use Matlab simulation analysis of the performance of these algorithms
capacity-of-ZF-and-MRT
- 关于MIMO天线的matlab仿真，有代码和仿真结果图-Matlab simulation on MIMO antenna with code and the simulation results
wireless communication
- MIMO通信，VBlast串行干扰抵消，结合ZF算法和MMSE算法，比较其性能。MIMO通信 串行干扰抵消(MOMO communication, serial interference cancellation)
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