DocumentCode :
1615021
Title :
Neural Network Nonlinear MIMO Channel Identification and Receiver Design
Author :
Al-Hinai, A. ; Ibnkahla, M.
Author_Institution :
Dept. of Electr. & Comput. Eng., Queen´´s Univ. Canada, Kingston, ON
fYear :
2008
Firstpage :
835
Lastpage :
839
Abstract :
Multiple-input multiple-output (MIMO) systems have gained an enormous amount of attention as one of the most promising research areas of wireless communication. However, while MIMO systems have been extensively explored over the past decade, few schemes acknowledge the nonlinearity caused by the use of high power amplifiers (HPAs) in the communication chain. When HPAs operate near their saturation points, nonlinear distortions are introduced in the transmitted signal, and the resulting MIMO channel will be nonlinear. The nonlinear distortion is further exacerbated by the fading caused by the propagation channel. The goal of this paper is to use neural network (NN) technique for modeling and identification of time-varying nonlinear MIMO channels. NN schemes are then used to design an efficient receiver for these types of nonlinear fading MIMO channels.
Keywords :
MIMO communication; channel allocation; fading channels; neural nets; nonlinear distortion; radio receivers; telecommunication computing; time-varying channels; MIMO channel identification; fading channel; high power amplifiers; multiple-input multiple-output systems; neural network nonlinear identification; nonlinear distortion; propagation channel; receiver design; saturation points; time-varying nonlinear MIMO channels; wireless communication; Communications Society; Detection algorithms; Fading; High power amplifiers; MIMO; Neural networks; Nonlinear distortion; Signal to noise ratio; Transfer functions; Wireless communication;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Communications, 2008. ICC '08. IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-2075-9
Electronic_ISBN :
978-1-4244-2075-9
Type :
conf
DOI :
10.1109/ICC.2008.164
Filename :
4533200
Link To Document :
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