Paper Info
Title
An ordinal optimization like GA for improved OFDMA system carrier allocations
Abstract
Different intelligent techniques have been proposed to solve the downlink resource allocation in orthogonal frequency division multiple access (OFDMA)-based networks. These include mathematical optimization, game theory and heuristic algorithms. In an attempt to improve the performance of traditional genetic algorithm (GA), we propose a novel improved GA (IGA) which uses a new mutation operator as well as adopts concepts of ordinal optimization (OO) for selecting GA parameters such as the initial population and the stopping criteria in a manner that meets the quality of service requirements for different types of OFDMA users despite the large search space. Performance of IGA over different fitness functions published in literature, shows improved resource allocation results over regular GA and motivates follow on research.
Year
DOI
Venue
2012
10.1109/IS.2012.6335170
IEEE Conf. of Intelligent Systems
Keywords
Field
DocType
OFDM modulation,frequency division multiple access,game theory,genetic algorithms,quality of service,IGA,OFDMA system carrier allocation,OFDMA-based network,downlink resource allocation,fitness function,game theory,genetic algorithm,heuristic algorithm,mathematical optimization,mutation operator,ordinal optimization,orthogonal frequency division multiple access,quality of service,Genetic Algorithm,OFDMA,Ordinal Optimization,Scheduling
Population,Mathematical optimization,Heuristic,Scheduling (computing),Computer science,Orthogonal frequency-division multiple access,Theoretical computer science,Resource allocation,Frequency-division multiple access,Ordinal optimization,Genetic algorithm
Conference
ISBN
Citations 
PageRank 
978-1-4673-2276-8
0
0.34
References 
Authors
5
2
Name
Order
Citations
PageRank
Nader El-Zarif100.34
Mariette Awad2685.71