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A stack-based sequential depth-first decoder that returns Maximum-Likelihood solutions to spherical LAST coded MIMO system-type problems
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单用户MIMO以及多用户MIMO的检测程序,包括最大似然检测,最小均方误差检测等的matlab实现,以及MIMO_OFDM主要程序-Single-user MIMO and multi-user MIMO testing procedures, including maximum likelihood detection, minimum mean square error detection matlab realize and the main program of MIMO_OFDM
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2X2 MIMO系统使用ML(最大似然)接受。(验证可用)-2X2 MIMO system using the ML (maximum likelihood) to accept. (Verification can be used)
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《通信信道处理》课程设计,内容为MIMO系统的性能仿真分析,内含MIMO系统的构建、Rayleigh信道、AWGN干扰、QPSK调制解调等,按照IEEE格式全英书写,请大家多多指教-Performance Analysis of Maximum Likelihood Detection in a MIMO Antenna System.pdf
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MIMO无线传输 无线传输 无线传输 -MIMO transmission model, JAKAFANI Quasi orthogonal space time block codes with four transmit and one receive antenans over flat fading channel with maximum likelihood detector (ML)
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The results for 2×2 MIMO with Maximum Likelihood (ML) equalization helped us to achieve a performance closely matching the 1 transmit 2 receive antenna Maximal Ratio Combining (MRC) case.
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Maximum Likelihood equalization for STBC-MIMO systems
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The main goal of this work is to provide a unified theory of QSTBCs for four transmit antennas and
one (or more) receive antennas. The thesis consists of two main parts: In the first part we analyze the
QSTBCs transmission without any channel kno
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该函数可以实现在mimo信号传输时的波束矩阵,尽可以实现在线性接收机的情况下可以达到最大似然的性能,从而大大简化接收机的设计。-This function can be achieved when the signal transmission in mimo beam matrix can make the case of linear receiver can achieve the maximum likelihood performance, which greatly simplify
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MIMO 最大似然算法代码 自己写的 仅做参考-MIMO maximum likelihood algorithm code
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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
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多天线正交频分复用(MIMO-OFDM,Multiple-Input and Multiple-Output Orthogonal Frequency Division Multiplex)系统中,精确的符号定时同步可使接收端解调数据时消除载波频率偏移和符号间干扰。而由于MIMO空间信道复杂度较高,使得单天线OFDM系统的同步方法不能直接应用于MIMO-OFDM系统中。提出的两步同步方法首先利用时域导频作为第一步同步进行粗同步,然后利用循环交织前缀作为第二步同步对每一个MIMO-OFDM符号进行
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最大似然检测的相关程序,用于单用户MIMO,初学编程-Maximum likelihood detection procedures for single-user MIMO, novice programming
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多入多出(MIMO)系统可以获得比单发单收系统更高的容量,对于MIMO系统,最大似然检测是最优接收,但其
指数复杂度难以在实际中应用。针对该问题,结合格缩减理论提出了基于Householder变换的复数域格缩减算法,将该算法和
MIMO次优检测算法相结合,给出了量化判决方法,且该复数域格缩减算法复杂度小于实数域格缩减算法。仿真结果表明,
基于Householder变换复数域格缩减的MIMO次优检测算法,通过优化信道矩阵可以得到更好的判决域,取得了逼近最优最大
似然检测算法的性能。
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VC2010及IT++4.2下实现MIMO的仿真-This example demonstrates how to use the Modulator_ND (MIMO) class for soft-output demodulation. The program simulates a simple convolutionally coded spatial-multiplexing (V-BLAST style) MIMO system with maximum-likelihood, a
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MIMO系统中4发送4接收的最大似然检测算法,可自行扩展到其他发送结构-MIMO systems send four received the maximum likelihood detection algorithm, they are free to expand to other transmit architecture
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在平稳瑞利多径信道下,用BPSK调制,用matlab 仿真由最大似然译码的性能。-It discuss a receiver structure called Maximum Likelihood (ML) decoding which gives us a better performance. We will assume that the channel is a flat fading Rayleigh multipath channel and the modulation is BP
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基于Matlab的MIMO通信系统仿真,使用最大似然译码准则。适合初学者使用-Simulation of MIMO communication system based on Matlab, using the maximum likelihood decoding criterion. Suitable for beginners to use
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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
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Maximum likelihood detection for MIMO. all supporting file
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