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
收藏
页码：4667 / 4672
页数：7
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