Memory Binary Particle Swarm Optimization (MBPSO) Applied to a Spectrum Sharing Problem

Anabel Martínez-Vargas, Ángel G. Andrade, Guillermo Galaviz


Spectrum sharing is one of the solutions for Heterogeneous Networks (HetNets) for achieving additional spectral resource. The aim is to promote the coexistence of different radio systems in the same spectral portion increasing the spectral efficiency of the HetNet, but at teh same time the interference is increased. In this paper, we tackle with the problem of spectrum sharing in a HetNet composed of a macrocell and several femtocells. We propose a strategy, in which macrocell and femtocells can share simultaneously the available bandwidth while avoiding intra-tier interference. Our approach is formulated as a binary optimization problem. The fitness is evaluated considering techniques of binary optimization with memory to overcome the problem of premature convergence or loss of diversity that Socio-Cognitive Particle Swarm Optimization (SCPSO) presents. The results show that by using the Memory Binary Particle Swarm Optimization (MBPSO) algorithm, the system’s capacity is improved in comparison with solutions obtained using SCPSO. Also the performance of MBPSO is compared with Angle Modulated PSO (AMPSO) and Modified BPSO (ModBPSO) algorithms.



Spectrum sharing, spectral efficiency, heterogeneous networks, MBPSO.

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