A Near-ML Decoding with Improved Complexity over Wider Ranges of SNR and System Dimension in MIMO Systems

被引：3
作者：
Ahn, Junil [1 ]
Lee, Heung-No [1 ]
Kim, Kiseon [1 ]
机构：
[1] Gwangju Inst Sci & Technol GIST, Sch Informat & Mechatron SIM, Kwangju, South Korea
来源：
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS | 2012年 / 11卷 / 01期
基金：
新加坡国家研究基金会;
关键词：
Multiple-input-multiple-output (MIMO) detection; sphere decoding (SD); near-maximum-likelihood decoding; lattice decoding; LATTICE; SEARCH; REDUCTION;
D O I：
10.1109/TWC.2011.110811.110471
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
In this letter, we aim to present a near-maximum-likelihood (ML) decoding algorithm with low-complexity for wider ranges of SNR and system dimension in multiple-input-multiple-output (MIMO) systems. Based on the proposed radius design criterion, we introduce the effective radius (ER) which is determined using the statistics of path metric under correct and incorrect decoding cases. Since the constraint established by the ER maintains tightness during most search procedure, the proposed scheme further improves the complexity, and its performance loss is still negligible by properly selecting design probabilities.
引用
收藏
页码：33 / 37
页数：5
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