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
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
V-BLASTSystem
- 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 V-BLAST system and its detection algorithm of the simulation, can be used BPSK, QPSK, 16QAM, 64QAM modulation. Detection algorithm for the ML, MMS
ML_algorithm
- MIMO系统中进行信道估计的原始代码，Matlab格式。-code with matlab format for channel estimation in MIMO system
MIMO-OFDM-ML
- Multiple Input Multiple Output (MIMO) Orthogonal Frequency Division Multiplexing (OFDM) Maximum Like lihood (ML)
MIMO
- 自己改写的MIMO系统中进行ML,MSE,ZF3种estimation，并比较-in the MIMO system, realize the ML,MSE,ZF estimator, and compare them
ML-versus-LS
- 这是关于基于MIMO-OFDM的同步算法的研究的程序，本程序使用的是最简单的方法，即ML算法。-This is about based on mimo-ofdm synchronization algorithm research program, this program is using the most simple method, namely ML algorithm.
mimo
- 仿真不同MIMO接收机算法的误码率，包括MMSE、ML、迫零法-MIMO receiver algorithms for simulation of different BER, including MMSE, ML, zero forcing
MIMO_detection
- MIMO 检测仿真 ML MMSE ZF 还有OSIC的-MIMO detector simulation ML MMSE ZF OSIC' s there
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
BER-for-BPSK--ZF--ML-2-2
- mimo 2*2 ,采用BPSK调制，内含ZF，MMSE检测算法。-mimo 2* 2,using BPSK modulation, containing ZF, MMSE 1detection algorithm.
luilan
- ML法能够很好的估计信号的信噪比,MIMO OFDM matlab仿真,欢迎大家下载学习。- ML estimation method can be a good signal to noise ratio, MIMO OFDM matlab simulation, Welcome to download the study.
tanghou_v27
- 最大似然（ML）准则和最大后验概率（MAP）准则，MIMO OFDM matlab仿真,LZ复杂度反映的是一个时间序列中。- Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, MIMO OFDM matlab simulation, LZ complexity is reflected in a time sequence.
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)
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