An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation

An operational economic model for radio resource allocation in the downlink of a multi-cell WCDMA (acronym for wideband code division multiple access). system is developed in this paper, and a particle swarm optimization (PSO) based approach is proposed for its solution. Firstly, we develop an econo...

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Bibliographic Details
Published in:Electronic commerce research 2014-03, Vol.14 (1), p.51-70
Main Authors: Mattos, César L. C., Barreto, Guilherme A., Cavalcanti, Francisco R. P.
Format: Article
Language:English
Subjects:
Algorithms
Analysis
Business and Management
Code Division Multiple Access
Communications systems
Computer Communication Networks
Data Structures and Information Theory
e-Commerce/e-business
Economic analysis
Economic aspects
Economic models
Economics
Genetic algorithms
IT in Business
Mathematical models
Mathematical optimization
Multimedia
Operations Research/Decision Theory
Optimization algorithms
Optimization techniques
Pricing policies
Quality of service
Radio
Resource allocation
Spectrum allocation
Studies
Swarm intelligence
Utility functions
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Summary:An operational economic model for radio resource allocation in the downlink of a multi-cell WCDMA (acronym for wideband code division multiple access). system is developed in this paper, and a particle swarm optimization (PSO) based approach is proposed for its solution. Firstly, we develop an economic model for resource allocation that considers the utility of the provided service, the acceptance probability of the service by the users and the revenue generated for the network operator. Then, we introduce a constrained hybrid PSO algorithm, called improved hybrid particle swarm optimization (I-HPSO), in order to find feasible solutions to the problem. We compare the performance of the I-HPSO algorithm with those achieved by the original HPSO algorithm and by standard metaheuristic optimization techniques, such as hill climbing, simulated annealing, standard PSO and genetic algorithms. The obtained results indicate that the proposed approach achieves superior performance than the conventional techniques.
ISSN:1389-5753
1572-9362
DOI:10.1007/s10660-013-9128-x