Statistical Analysis of Steepest Descend and LMS Detection Algorithms for MIMO Systems

被引：3

作者：

Zanella, Alberto ^{[1
]}

Chiani, Marco ^{[2
]}

Win, Moe Z. ^{[3
]}

机构：

[1] Natl Res Council Italy, Inst Elect Comp & Telecommun Engn, I-40136 Bologna, Italy

[2] Univ Bologna, Dept Elect Comp Sci & Syst, I-40136 Bologna, Italy

[3] MIT, Lab Informat & Decis Syst, Cambridge, MA 02139 USA

来源：

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY | 2011年 / 60卷 / 09期

基金：

美国国家科学基金会;

关键词：

Least square mean (LMS) algorithm; multiple-input multiple-output (MIMO); steepest descent (SD) algorithm; Wishart matrices;

D O I：

10.1109/TVT.2011.2170185

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：

We study the performance of steepest descent (SD) and least mean square (LMS) algorithms applied to linear detection for multiple-input multiple-output (MIMO) systems in a correlated Rayleigh fading environment. By using random matrix theory, we first study stability for a fixed step size parameter. Then, we consider two always-stable channel-adaptive strategies for the choice of the step size and analytically evaluate their performance. Finally, we derive bounds on the mean value of misadjustment for the LMS algorithm.

引用

页码：4667 / 4672

页数：7

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