An Improved QRD-M Detection Algorithm for MIMO Communication System

Li Liu, Jinkuan Wang, Dongmei Yan, Bin Wang
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引用次数: 3

Abstract

QR decomposition based M-algorithm (QRD-M) can provide near maximum likelihood detection (MLD) performance and low complexity for MIMO communication. The QRD-M algorithm reduces the complexity by selecting M candidates with the smallest accumulated metrics at each level of the tree search. The trade-off between performance and complexity can be adjusted only by setting the parameter M which cannot provide more valuable tradeoff options with better performance to complexity ratio. Based on the equivalent QRD-M model, a new detection scheme is proposed in this paper for MIMO system on flat fading channel. The detection scheme, named as improved QRD-M (IQRD-M) with two independent parameters, is composed of two parts. After performing QR decomposition of the channel matrix, the MLD with length P is done, the accumulated metrics are calculated and sorted, which gives an ordered set, then IQRD-M algorithm is used to search the left layers with novel termination methods. The proposed algorithm provides better tradeoff options and more near-ML performance with low complexity.
一种改进的MIMO通信系统QRD-M检测算法
基于QR分解的m -算法(QRD-M)可以为MIMO通信提供接近最大似然检测(MLD)的性能和较低的复杂度。QRD-M算法通过在树搜索的每个层次上选择M个累积指标最小的候选树来降低复杂度。性能和复杂度之间的权衡只能通过设置参数M来调整,而M不能提供更有价值的权衡选项和更好的性能复杂度比。基于等效QRD-M模型,提出了一种基于平坦衰落信道的MIMO系统检测方案。该检测方案命名为改进型双参数QRD-M (IQRD-M),由两部分组成。对信道矩阵进行QR分解后,得到长度为P的MLD,对累积的度量进行计算和排序,得到有序集,然后利用IQRD-M算法对左层进行搜索,并采用新颖的终止方法。该算法提供了更好的权衡选项和更接近机器学习的性能,且复杂度低。
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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