A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA

Aydin, Mehmet E.; Aydin, Mehmet Emin; Kwan, Raymond; Leung, Cyril; Maple, Carsten; Zhang, Jie

Abstract

Multiuser scheduling is an important aspect in the performance optimization of a wireless network since it allows multiple users to access a shared channel efficiently by exploiting multiuser diversity. To perform efficient scheduling, channel state information (CSI) for users is required, and is obtained via their respective feedback channels. In this paper, a more realistic imperfect CSI feedback, in the form of a finite set of Channel Quality Indicator (CQI) values, is assumed as specified in the HSDPA standard. A mathematical model of the problem is developed for use in the optimization process. A hybrid heuristic approach based on particle swarm optimization and simulated annealing is used to solve the problem. Simulation results indicate that the hybrid approach outperforms individual implementations of both simulated annealing and particle swarm optimization. © 2011 Elsevier B.V. All rights reserved.

Citation

Aydin, M. E., Aydin, M. E., Kwan, R., Leung, C., Maple, C., & Zhang, J. (2013). A hybrid swarm intelligence algorithm for multiuser scheduling in HSDPA. Applied Soft Computing, 13(5), 2990-2996. https://doi.org/10.1016/j.asoc.2011.12.007

• Journal Article Type: Article
• Publication Date: Jan 1, 2013
• Journal: Applied Soft Computing Journal
• Print ISSN: 1568-4946
• Publisher: Elsevier
• Peer Reviewed: Peer Reviewed
• Volume: 13
• Issue: 5
• Pages: 2990-2996
• DOI: https://doi.org/10.1016/j.asoc.2011.12.007
• Keywords: particle swarm optimization, simulated annealing, hybrid swarm intelligence, multiuser scheduling resource allocation
• Public URL: https://uwe-repository.worktribe.com/output/932195
• Publisher URL: http://dx.doi.org/10.1016/j.asoc.2011.12.007