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

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Abstract

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.

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Notes

  1. Acronim for global system for mobile communications.

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Authors and Affiliations

  1. Department of Teleinformatics Engineering, Federal University of Ceará, Av. Mister Hull, S/N, Campus of Pici, Center of Technology, CP 6005, CEP 60455-970, Fortaleza, Ceará, Brazil

    César L. C. Mattos, Guilherme A. Barreto & Francisco R. P. Cavalcanti

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  1. César L. C. Mattos
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  2. Guilherme A. Barreto
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  3. Francisco R. P. Cavalcanti
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Correspondence to Guilherme A. Barreto.

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Mattos, C.L.C., Barreto, G.A. & Cavalcanti, F.R.P. An improved hybrid particle swarm optimization algorithm applied to economic modeling of radio resource allocation. Electron Commer Res 14, 51–70 (2014). https://doi.org/10.1007/s10660-013-9128-x

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