Turbo-learning: A novel application to MIMO wireless communications

被引:0
|
作者
Haykin, S [1 ]
Sellathurai, M [1 ]
机构
[1] McMaster Univ, Hamilton, ON L8S 4L8, Canada
关键词
communication system; convergence problem; feedback; information; likelihood function; Markov model;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper briefly reviews the turbo-learning principle, thereby setting the stage for the description of a novel multiple-input, multiple-output (MIMO) wireless communication system. This new system, called Turbo-BLAST, builds on two key principles: (.)The Turbo-learning principle (.)The Bell-Labs Space-Time Layered (BLAST) architecture Experimental results are presented, demonstrating the high-spectral efficiency of Turbo-BLAST. A distinctive feature of the Turbo-BLAST receiver is its rapidly converging iterative nature. Indeed, it may be described as a nonlinear stochastic sampled-data feedback system. The paper identifies the development of a mathematical framework for convergence analysis of the receiver as an open research problem. Copyright (C) 2001 IFAC.
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页码:315 / 324
页数:10
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