Home > Published Issues > 2023 > Volume 18, No. 6, June 2023 >
JCM 2023 Vol.18(6): 377-384
Doi: 10.12720/jcm.18.6.377-384

Coverage Optimization of Eureka Digital Sound Broadcasting Single Frequency Network Using Simulated Annealing and Particle Swarm Optimization

Joseph Sospeter Salawa1,*, Elijah Mwangi2, and Nerey Mvungi3
1.Department of Electrical Engineering, Pan African University Institute of Science Technology and Innovation, Nairobi, Kenya
2.School of Engineering, University of Nairobi, Nairobi, Kenya
3.College of Information and Communication Technologies, University of Dar es Salaam, Tanzania
*Correspondence: yusufujss@gmail.com (J.S.S.)

Manuscript received October 1, 2022; revised October 27, 2022; accepted January 30, 2023.

Abstract—Due to scarcity of bandwidth available for sound broadcasting, Digital sound broadcasting Technology is emerging to be the Technology of resort in sound broadcasting industry towards replacing the analogue sound broadcasting currently dominated by FM Radio. There are many digital sound broadcasting systems being proposed with different performance and bandwidth efficiency. Static delays are artificial delays intentionally introduced at each Transmitter in order to minimize interference in a Single Frequency Network (SFN). In this paper, we have looked at the Terrestrial digital audio broadcasting (T-DAB) system specifically to optimize its final SFN coverage by finding an optimal set of static delays for transmitters. For the sake of simulation, hexagonal model of transmitters operating under Single Frequency Network (SFN) was used. The aim of this study is to maximize SFN coverage by using optimal set of artificial static delays, Particle Swarm Optimization (PSO) have strong ability in finding the global optimistic result while Stimulated Annealing (SA) algorithm has a strong ability to find the local Optimistic result and therefore based on their unique strength, these methods were selected so that our study can have a good comparison in terms of coverage by using both global and local optimistic results. We report the increase of coverage by 1.12% and 2.38% using Simulated Annealing and Particle Swarm Optimization technique respectively.

Keywords—Digital audio broadcasting, particle swarm optimization, simulated annealing, artificial static delays .

Cite: Joseph Sospeter Salawa, Elijah Mwangi, and Nerey Mvungi, "Coverage Optimization of Eureka Digital Sound Broadcasting Single Frequency Network using Simulated Annealing and Particle Swarm Optimization," Journal of Communications vol. 18, no. 6, pp. 377-384, June 2023. 

Copyright © 2023 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.