Real Coded Genetic Algorithm with Enhanced Abilities for Adaptation Applied to Optimisation of MIMO Systems

Gergana Yalamova, Georgi Iliev, Kalin Penev

Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review

Abstract

This article presents an investigation of real coded Genetic Algorithm Blend Crossover Alpha modification, with enhanced ability for adaptation, applied to minimisation of transmit power in multiple-input multiple-output (MIMO) systems beamforming. The goal is to formulate transmit power minimisation task as a black box software object and evaluate an alternative to currently existing methods for optimisation of transmit energy in multicast system constrained by signal to noise ratio. The novelty of this adaptive methodology for determination of minimal power level within certain Quality of Service criteria is that it guarantees satisfaction of the constraint and 100% feasibility of achieved solutions. In addition this methodology excludes retuning algorithms parameters by using black box model for the problem definition. Experiments are conducted for identification of weight vectors assigned for signal strength and direction. Achieved experimental results are presented and analysed.
Original languageEnglish
Title of host publicationOptimisation of Mobile Communication Networks. Southampton Solent University, UK
Place of PublicationUK
PublisherSouthampton Solent University
Pages41-49
Number of pages9
ISBN (Print)978-0-9563140-4-8
Publication statusPublished - 1 Jun 2012

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