ABC-PLOSS: a software tool for path-loss minimisation in GSM telecom networks using artificial bee colony algorithm. (2019)

• Record Type: Journal Article
• Authors: Anireh, Vincent Ike E.; Osegi, Emmanuel Ndidi
• Is Part Of: International journal of swarm intelligence. Volume 4:Number 1(2019)
• Page Start: 20
• Page End: 37
• Publication Date: 2019
• Subjects: artificial bee colony -- ABC -- improvement factor -- minimisation -- path-loss -- telecommunication networks -- global system mobile -- GSM; Swarm intelligence -- Periodicals; 006.3
• Languages: English
• ISSNs: 2049-4041

Abstract

In this paper, we present an open-source software tool 'ABC-PLOSS', which is developed for use in optimisation processes. Path-loss optimisation deals with searching for the best set of operator-specific parameters in telecommunication that gives the least cost of operation. It is a primary issue that challenges mobile communication operators, particularly the global system mobile (GSM) operators in tuning mobile-base station networks for efficient and reliable operation. The tool uses a sequential processor architecture based on a swarm intelligence algorithm called artificial bee colony (ABC) and the cost-231 Hata path-loss model as cost function for path-loss minimisation (PLM). Using the ABC-PLOSS framework, the ABC algorithm is compared with two other existing and popular artificial intelligent (AI) algorithms called the genetic algorithm (GA) and particle swarm optimisation (PSO). Results of simulation studies show that this tool is indeed useful as it gives a competitive or lower path-loss estimate when compared with conventional techniques. It also shows that it is possible for the ABC to attain an estimated seven-fold and two-fold path-loss improvement over the GA and the PSO techniques respectively.