Indoor Antenna Placement Automation with Meta-heuristic Optimization

This paper presents a novel framework, Antenna Placement Simulator and Optimizer (APSO), for antenna placement optimization using meta-heuristic algorithms and MATLAB simulation. APSO addresses realistic scenarios, including 3D en-vironments and non-line-of-sight (NLOS) conditions, optimizing antenna placement for criteria such as path loss and received power. A fitness function is devised to find optimal positions and balance power distribution. The framework is evaluated using two meta-heuristic algorithms, Genetic Algorithm (GA) and Particle Swarm Optimization (PSO), with results highlighting their respective strengths and weaknesses. Finally, an adaptive algorithm is proposed for dynamic antenna relocation based on receiver positions, demonstrating its effectiveness in changing scenarios and revealing its unique advantages and limitations.