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Local Search is Underused in Genetic Programming

Abstract

This paper presents a genetic programming (GP) approach enhanced with a local search heuristic (GP-LS) to emulate the Doherty 7 W @ 2.11 GHz Radio Frequency (RF) Power Amplifier (PA) conversion curves. GP has been shown to be a powerful modeling tool, but can be compromised by slow convergence and computational cost. The proposal is to combine the explorative search of standard GP, which build the syntax of the solution, with numerical methods that perform an exploitative and greedy local optimization of the evolved structures. The results are compared with traditional modeling techniques, particularly the memory polynomial model (MPM). The main contribution of the paper is the design, comparison and hardware emulation of GP-LS for FPGA real applications. The experimental results show that GP-LS can outperform standard MPM, and suggest a promising new direction of future work on digital pre-distortion (DPD) that requires complex behavioral models.

Publication
In Genetic Programming Theory and Practice XIV.
Date
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