Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article A Simplified Constant Modulus Algorithm for Blind Recovery of MIMO QAM and PSK Signals: A Criterion with Convergence Analysis | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2007 Article ID 90401 13 pages doi 2007 90401 Research Article A Simplified Constant Modulus Algorithm for Blind Recovery of MIMO QAM and PSK Signals A Criterion with Convergence Analysis Aissa Ikhlef and Daniel Le Guennec IETR SUPELEC Campus de Rennes Avenue de la Boulaie CS 47601 35576 Cesson-Sevigne France Received 31 October 2006 Revised 18 June 2007 Accepted 3 September 2007 Recommended by Monica Navarro The problem of blind recovery of QAM and PSK signals for multiple-input multiple-output MIMO communication systems is investigated. We propose a simplified version of the well-known constant modulus algorithm CMA named simplified CMA SCMA . The SCMA cost function consists in projection of the MIMO equalizer outputs on one dimension either real or imaginary part . A study of stationary points of SCMA reveals the absence of any undesirable local stationary points which ensures a perfect recovery of all signals and a global convergence of the algorithm. Taking advantage of the phase ambiguity in the solution of the new cost function for QAM constellations we propose a modified cross-correlation term. It is shown that the proposed algorithm presents a lower computational complexity compared to the constant modulus algorithm CMA without loss in performances. Some numerical simulations are provided to illustrate the effectiveness of the proposed algorithm. Copyright 2007 A. Ikhlef and D. Le Guennec. 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. 1. INTRODUCTION In the last decade the interest in blind source separation BSS techniques has been important. The problem of blind recovery of multiple independent and identically distributed . signals from their linear mixture in a multiple-input .
