A Base Station Deployment Optimization using Energy Efficiency for Networks with Integrated Access and Backhaul

Integrated access and backhaul (IAB) networks are a technology proposed in recent 3rd generation partnership project releases for 5th generation (5G)-new radio (NR) networks due to their potential to reduce deployment and backhauling costs, as well as to improve spectrum usage. In 5G networks (IAB ones included), it is necessary to solve the base station deployment problem for the installation and expansion of the network while ensuring good service quality. In this work, we optimize the positioning of base stations (BSs) using genetic algorithm (GA) and particle swarm optimization (PSO) having energy efficiency (EE) as the optimization metric. Different scenarios are considered, and the obtained results show that GA outperforms PSO in all the studied cases. The solutions found by the algorithms are analyzed using Monte Carlo simulations to evaluate mean EE and Signal to interference-plus-noise ratio (SINR) as key performance indicators, which suggest that a joint optimization could be carried out as to obtain a network with high communication quality and good EE.