An introduction to genetic algorithms
An introduction to genetic algorithms
Practical genetic algorithms
Multiuser Detection
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Convex Optimization
Performance evaluation of impulse radio UWB systems with pulse-based polarity randomization
IEEE Transactions on Signal Processing
The ultra-wide bandwidth indoor channel: from statistical model to simulations
IEEE Journal on Selected Areas in Communications
Time domain equalizer design using bit error rate minimization for UWB systems
EURASIP Journal on Wireless Communications and Networking
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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.