Genetic Algorithm for Base Station Placement in Integrated Access and Backhaul Networks

Fifth Generation networks aim to enhance many areas over their predecessor, the Fourth Generation, namely data rate increase, latency reduction, and spectrum usage efficiency. That is achieved through many techniques, such as network densification and the usage of Millimeter Wave, which introduce many new challenges in deployment. In this context, Integrated Access and Backhaul (IAB) technology is meant to increase these networks' flexibility and viability due to its cost-effectiveness, fast deployment, and easy maintenance. In this paper, we investigated the cost-effectiveness of IAB networks in terms of Spectral Efficiency (SE) by comparing, through simulation results, different scenarios with varying quantities of IAB nodes, to a benchmark one containing only Macro Base Stations (MBSs). For this purpose, the network deployment was optimized using a Genetic Algorithm (GA) in order to compare the different scenarios in a fair manner. The results have shown that the introduction of a number of IAB nodes into the network allows us to attain promising cost-efficiency trade-offs, achieving considerably reduced costs at the expense of minor reductions in performance.