A genetic approach for linear-quadratic channel identification with usual communication inputs

被引：1

作者：

Cherif, Imen ^{[1
]}

Abid, Sabeur ^{[1
]}

Fnaiech, Farhat ^{[1
]}

机构：

[1] ESSTT, Res Unit SICISI, Tunis 1008, Tunisia

来源：

2007 IEEE INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, VOLS 1-6 | 2007年

关键词：

blind identification; Volterra kernels; higher order statistics (HOS); genetic algorithm (GA); digital communication signals;

D O I：

10.1109/IJCNN.2007.4371214

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

The blind identification of a special class of nonlinear system is pursued in this paper. In particular a genetic algorithm is developed for the blind identification of linear-quadratic Volterra model excited by inputs commonly used in digital communication such as PSK and QAM signals. Since the cost function with higher order statistics has local minimum points, the use of genetic algorithm allows to escape from these last and to find an optimal solution of the identified channel. Several simulations are performed and show a fair accuracy given sufficiently long observation records.

引用

页码：1703 / 1707

页数：5

共 14 条

[1] ANALYSIS AND COMPENSATION OF NONLINEARITIES IN DIGITAL TRANSMISSION-SYSTEMS [J].