Optimal and Suboptimal Finger Selection Algorithms for MMSE Rake Receivers in Impulse Radio UWB Systems

TL;DR

This paper develops and compares optimal, suboptimal, and genetic algorithm-based finger selection methods for MMSE Rake receivers in impulse radio UWB systems, improving performance over conventional methods.

Contribution

It introduces convex relaxation and genetic algorithm approaches for finger selection, achieving near-optimal performance with practical complexity.

Findings

Proposed algorithms outperform conventional finger selection.

Genetic algorithm achieves near-optimal performance.

Convex relaxation methods improve finger selection accuracy.

Abstract

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 non-convex 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.