Particle Swarm Optimization (PSO)-Based Distributed Power Control Algorithm for Wireless Radio Systems

  • M. Abdulkadir Department of Electrical and Electronics Engineering, University of Maiduguri, Maiduguri, Nigeria
  • Z. M. Gwoma Department of Electrical and Electronics Engineering, University of Maiduguri, Maiduguri, Nigeria
  • A. B. Buji Department of Electrical and Electronics Engineering, University of Maiduguri, Maiduguri, Nigeria

Abstract

Power control in wireless radio system has been explored since the early 1990’s. Many researchers have developed algorithms to address problem of power control. Most of the algorithms in recent consider either the problem of minimizing the sum of transmitted power under quality of service (QoS) constraints given in terms of minimum carrier-to-interference ratio (CIR) in a static channel or the problem of mitigating fast fading in a single dynamic link. In this paper, a new approach to the power control was develop by treating the QoS requirement as another objective for the power control and the resulting constrained multi-objective-objective optimization problem is solved by means of particle swarm optimization (PSO).The convergence properties of the proposed algorithm are studied both theoretically and with numerical simulations. Noisy, dynamical environment is assumed in the simulations. The algorithm was modified to take throughput into consideration. Simulations demonstrated that the proposed power control algorithms converged faster than the conventional power control algorithms. Also, the average transmitted power was less than the average transmitted power using the conventional methods with comparable Quality of Service (QoS).

Published
Dec 1, 2017
How to Cite
ABDULKADIR, M.; GWOMA, Z. M.; BUJI, A. B.. Particle Swarm Optimization (PSO)-Based Distributed Power Control Algorithm for Wireless Radio Systems. Arid Zone Journal of Engineering, Technology and Environment, [S.l.], v. 13, n. 6, p. 688-700, dec. 2017. ISSN 2545-5818. Available at: <http://azojete.com.ng/index.php/azojete/article/view/268>. Date accessed: 27 may 2018.
Section
Articles