TAILIEUCHUNG - Báo cáo sinh học: " Research Article A Gaussian Mixture Approach to Blind Equalization of Block-Oriented Wireless Communications Frederic Lehmann (EURASIP Member)"

Tuyển tập các báo cáo nghiên cứu về sinh học được đăng trên tạp chí sinh học Journal of Biology đề tài: Research Article A Gaussian Mixture Approach to Blind Equalization of Block-Oriented Wireless Communications Frederic Lehmann (EURASIP Member) | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2010 Article ID 340417 10 pages doi 2010 340417 Research Article A Gaussian Mixture Approach to Blind Equalization of Block-Oriented Wireless Communications Frederic Lehmann EURASIP Member Institut TELECOM TELECOM SudParis Department CITI UMR-CNRS 5157 91011 Evry Cedex France Correspondence should be addressed to Frederic Lehmann Received 6 October 2009 Revised 12 May 2010 Accepted 30 June 2010 Academic Editor Tim Davidson Copyright 2010 Frederic Lehmann. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. We consider blind equalization for block transmissions over the frequency selective Rayleigh fading channel. In the absence of pilot symbols the receiver must be able to perform joint equalization and blind channel identification. Relying on a mixed discrete-continuous state-space representation of the communication system we introduce a blind Bayesian equalization algorithm based on a Gaussian mixture parameterization of the a posteriori probability density function pdf of the transmitted data and the channel. The performances of the proposed algorithm are compared with existing blind equalization techniques using numerical simulations for quasi-static and time-varying frequency selective wireless channels. 1. Introduction Blind equalization has attracted considerable attention in the communication literature over the last three decades. The main advantage of blind transmissions is that they avoid the need for the transmission of training symbols and hence leave more communication resources for data. The pioneering blind equalizers proposed by Sato 1 and Godard 2 use low-complexity finite impulse response filters. However these methods suffer from local and slow convergence and may

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