Phenotypic and Genotypic Evolutionary Computation Power Control Algorithms in CDMA Cellular Radio Networks

Abstract

This paper has proposed the distributed power control (PC) algorithms that employ two evolutionary computation (EC) or genetic algorithm (GA) techniques in order to solve linear systems of equations for power update in CDMA cellular radio systems. The proposed algorithms are modeled on applying evolutionary computation algorithms with the phenotypic and genotypic views to the CDMA power control problem. The major gain from the applied evolutionary computation algorithms is more rapid optimization on linear systems of equations compared with the simple genetic algorithm (SGA). Employing the distributed constrained power control (DCPC) and bang-bang (BB) algorithms as the basic reference algorithms, we have designed and implemented computational experiments on the DS-CDMA system. The proposed EC-DCPC phenotypic algorithm is compared with the DCPC algorithm. The GA-DCPC genotypic algorithm is also compared with the BB algorithm used in the IS-95 and the W-CDMA systems. The simulation results indicate that the proposed EC-DCPC phenotypic and GA-DCPC genotypic algorithms significantly decrease the mobile terminal power consumption compared with the DCPC and BB algorithms, respectively. The calculation results show that our proposed EC-DCPC phenotypic and GA-DCPC genotypic algorithms also have a high potential advantage for increasing the CDMA cellular radio network capacity.