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在码分多址系统中,求解多用户检测问题是重要环节,介绍了多用户检测问题的应用背景和发展
现状,重点综述基于半定规划模型寻求多用户检测问题次优解的几种重要方法,包括随机扰动法、
坐标下降法、半定规划的割平面法和二次规划的分枝定界法等。结合数值实验,评析比较了这些
方法的优缺点-Quasi-Maximum-Likelihood Multiuser Detection
Using Semi-Definite Relaxation With Application
to Synchro
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球形检测算法论文,性能接近最大似然算法,但是复杂度较低-Spherical detection algorithm paper, the performance near the maximum likelihood algorithm, but the complexity is low
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几种 MIMO 最大似然检测算法性能与复杂度比较及改进,介绍了半定松弛、分枝定界和堆栈三种低复杂度最大似然检测算法,并对其性能和复杂度进行了仿真分析,提出了改进的分枝定界和堆栈算法,仿真结果证明分枝定界和堆栈算法性能要优于半定松弛算法,分枝定界算法的复杂度低于堆栈算法且半定松弛算法以多项式复杂度取得了逼近最大似然的性能,同时改进算法加快了算法收敛速度,降低了计算复杂度和对存储空间的要求。
-Several maximum likelihood MIMO detection algorithm
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在多输入多输出系统中的鲁棒球形译码的实现-We present a maximum-likelihood decoding algorithm for an
arbitrary lattice code when used over an independent fading channel with
perfect channel state information at the receiver. The decoder is based on
a bounded distanc
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this file is concerning with maximum liklihood detection in digital communication
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code for maximum likelihood detection
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MIMO检测算法,联合多种调制方式,仿真对象为相应的误码率和容量等。-scr ipt for computing the BER for BPSK modulation in a Rayleigh fading channel with 2 Tx, 2Rx MIMO channel
Maximum Likelihood equalization
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曾峰的数字通信,主要包括波形成型,匹配滤波,AM调制解调,QPSK调制解调,FSK调制解调,最大似然检测等。-Digital communication has peaks, including waveform shaping, matched filtering, AM modulation and demodulation, QPSK modulation and demodulation, FSK modulation and demodulation, the maximum like
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研究无线信道优化问题, 由于非确定性 M MIO系统的信道矩阵行不满秩特性, 导致 MM SE- GDFE左预处理后引入了强干扰, 使得传统 K- Best算法产生了误码平层效应。为了消除误码平层效应,提出部分最大似然和 K - Best结合算法, 并在初始检测的强干扰区域利用部分最大似然算法获得局部最优解, 降低强干扰对系统的影响消除误码平层效应, 进而在局部最优解的基础上利用 K- Best算法完成剩余符号的检测, 保证 M MIO 检测器的软输出特性。仿真结果表明算法消除了传统 K- Be
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On Maximum-Likelihood Detection and the Search
for the Closest Lattice Point
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空间调制4*4天线bpsk方式下的最大似然检测-Spatial modulation 4* 4 antenna maximum likelihood detection bpsk under way
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ML detection for mimo ofdm
scr ipt for computing the BER for BPSK modulation in a
Rayleigh fading channel with 2 Tx, 2Rx MIMO channel
Maximum Likelihood equalization
-ML detection for mimo ofdm
scr ipt for computing the BER for BPSK modu
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Silicon Complexity for Maximum Likelihood MIMO
Detection Using Spherical Decoding
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MIMO 最大释然检测 (ML)Maximum likelihood equalizer for MIMO system-Maximum likelihood equalizer for MIMO system .MIMO ML detection,it s very useful
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Low complexity maximum likelihood MIMO signal detection algorithm
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基于分段非线性权重值的Pso算法,最大似然(ML)准则和最大后验概率(MAP)准则,有循环检测,周期性检测。- Based on piecewise nonlinear weight value Pso algorithm, Maximum Likelihood (ML) criteria and maximum a posteriori (MAP) criterion, There are cycle detection, periodic testing.
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