1Department of CSE-AIML, Netaji Subhash Engineering, Kolkata-700152, India
2CST Department, BPC Institute of Technology, Krishnanagar-741101, India
This study proposes a Grey Wolf Optimizer (GWO)-based framework for optimal base station (BTS) placement in wireless networks, minimizing infrastructure costs while maximizing coverage and Quality of Service (QoS). A multi-objective function simultaneously addresses: (1) minimal BTS deployment, (2) population coverage maximization, and (3) call failure reduction via reserved channel allocation. We introduce a novel binary-array solution encoding scheme and a weighted fitness function for GWO. Simulations across randomized and grid-based scenarios demonstrate superior performance over Genetic Algorithms (GA) and Particle Swarm Optimization (PSO), reducing BTS nodes by 25–30% and call failures by 50–60%. The framework offers a scalable solution for 5G/6G network planning.
Grey Wolf optimizer, Base stations, Mobile computing, Coverage, Potential positions, Call failure rate
