tailieunhanh - Báo cáo hóa học: " Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems"

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: Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2006 Article ID 84249 Pages 1-10 DOI WCN 2006 84249 Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems Sinan Gezici 1 Mung Chiang 2 H. Vincent Poor 2 and Hisashi Kobayashi2 1 Mitsubishi Electric Research Laboratories 201 Broadway Cambridge MA 02139 USA 2 Department of Electrical Engineering Princeton University Princeton NJ 08544 USA Received 16 September 2005 Revised 23 April 2006 Accepted 2 May 2006 The problem of choosing the optimal multipath components to be employed at a minimum mean square error MMSE selective Rake receiver is considered for an impulse radio ultra-wideband system. First the optimal finger selection problem is formulated as an integer programming problem with a nonconvex objective function. Then the objective function is approximated by a convex function and the integer programming problem is solved by means of constraint relaxation techniques. The proposed algorithms are suboptimal due to the approximate objective function and the constraint relaxation steps. However they perform better than the conventional finger selection algorithm which is suboptimal since it ignores the correlation between multipath components and they can get quite close to the optimal scheme that cannot be implemented in practice due to its complexity. In addition to the convex relaxation techniques a genetic-algorithm- GA- based approach is proposed which does not need any approximations or integer relaxations. This iterative algorithm is based on the direct evaluation of the objective function and can achieve near-optimal performance with a reasonable number of iterations. Simulation results are presented to compare the performance of the proposed finger selection algorithms with that of the conventional and the optimal schemes. Copyright 2006 Sinan Gezici et al. This is an open access article .