AI-Driven Optimization of Small Cell Deployment for Beyond 5G Networks
Eleni Aloupogianni, Charalampos Karyotis, Tomasz Maniak, Rahat Iqbal, Nikos Passas, Faiyaz Doctor, Zoran Vujičić
Abstract
The focus of this study is to examine how Artificial Intelligence (AI) influences the deployment of resources in the context of Beyond 5G (B5G) communications for modern applications. Employing a range of machine learning techniques, including neural networks and graph-based approaches, the investigation utilizes a small cell open dataset from the United States. The results highlight the exceptional performance of neural network models in streamlining small cell deployment, a pivotal aspect for improving both Internet of Things (IoT) connectivity and efficiency across expansive networks and critical applications. The study’s insights are relevant for telecommunications professionals and policymakers, offering practical perspectives on the transformative impact of AI in B5G scenarios within highly connected information systems.