COMPLEX-VALUED RADIAL BASIS FUNCTION NETWORK .2. APPLICATION TO DIGITAL-COMMUNICATIONS CHANNEL EQUALIZATION

被引：88

作者：

CHEN, S

MCLAUGHLIN, S

MULGREW, B

机构：

[1] Department of Electrical Engineering, University of Edinburgh, Edinburgh, EH9 3JL Scotland, King's Buildings, Mayfield Road

来源：

SIGNAL PROCESSING | 1994年 / 36卷 / 02期

关键词：

COMPLEX-VALUED RADIAL BASIS FUNCTION NETWORK; ADAPTIVE DECISION FEEDBACK EQUALIZERS; BAYES DECISION THEORY;

D O I：

10.1016/0165-1684(94)90206-2

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 [电气工程]; 0809 [电子科学与技术];

摘要：

In the first part of this paper, a complex-valued multi-output radial basis function network was proposed and two learning algorithms were derived. This second part investigates the adaptive realisation of a Bayesian solution for 4-QAM digital communications channel equalisation using the complex single-output radial basis function network. It is shown that the optimal Bayesian equaliser is structurally equivalent to the complex radial basis function network, and this intimate connection is exploited to develop fast training algorithms for implementing a Bayesian equaliser based on the latter. A novel strategy of utilising decision feedback is employed to improve equaliser performance as well as to reduce computational complexity. The conventional decision feedback equaliser and the maximum likelihood sequence estimator are used as two benchmarks to assess the performance of this Bayesian decision feedback equaliser.

引用

页码：175 / 188

页数：14

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