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This article is part of the series Ultra-Wideband Communication Systems: Technology and Applications.

Open Access Research Article

Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio Ultra-Wideband Systems

Sinan Gezici1*, Mung Chiang2, H Vincent Poor2 and Hisashi Kobayashi2

Author Affiliations

1 Mitsubishi Electric Research Laboratories, 201 Broadway, Cambridge, MA 02139, USA

2 Department of Electrical Engineering, Princeton University, Princeton, NJ 08544, USA

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EURASIP Journal on Wireless Communications and Networking 2006, 2006:084249  doi:10.1155/WCN/2006/84249


The electronic version of this article is the complete one and can be found online at: http://jwcn.eurasipjournals.com/content/2006/1/084249


Received:16 September 2005
Revisions received:23 April 2006
Accepted:2 May 2006
Published:22 June 2006

© 2006 Gezici et al.

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.

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.

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