减少了ML - MIMO系统的复杂性分析

2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN) Pub Date : 2013-03-25 DOI:10.1109/ICE-CCN.2013.6528529

R. Jothikumar

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引用次数: 2

摘要

在本文中，我们提出了一个简单的最大似然(ML)度量以及宽度优先树搜索算法，以减少解码MIMO(多输入多输出)系统传输符号时所需的操作数量和需要处理的节点数量。利用正交调幅(QAM)的相似特性，在不影响系统性能的前提下降低了系统的复杂度。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Reduced complexity analysis for ML MIMO systems

In this paper, we propose an uncomplicated Maximum Likelihood (ML) metric along with the breadth first tree search algorithm, to reduce the number of operations required and number of nodes to be processed while decoding the transmitted symbols of MIMO (Multiple Input Multiple Output) systems. Using the similarity property of the QAM (Quadrature Amplitude Modulation) the complexity of the system is reduced without compromising the performance.

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来源期刊

2013 IEEE International Conference ON Emerging Trends in Computing, Communication and Nanotechnology (ICECCN)

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