Adaptive Impedance Tuning Network using Genetic Algorithm: ITuneGA

Abstract

Adaptive impedance tuning algorithms are used to preserve the link quality of mobile phones under fluctuating user conditions. It is highly desirable to correct the complex impedance mismatch with high convergence rate. Presented here, is a novel technique for correcting impedance mismatch in adaptive impedance tuning network by exploiting the relationships among the genetic algorithm’s coefficient values derived from the matching network parameters. Simulation results demonstrate that the proposed impedance tunable algorithm (ITuneGA) outperforms conventional GA and LMS, with its fast convergence speed and high accuracy. The robustness of ITuneGA has been verified by using Pi-networks with two and four tuning elements. ITuneGA corrects antenna impedance mismatches and reduces the reflected power, thereby significantly improving the quality of the signal.