Maximizing throughput and energy efficiency in 6G based on phone user clustering enabled UAV assisted downlink hybrid multiple access HetNet

• Published in: Telecommunication systems 2024-04, Vol.85 (4), p.563-590
• Main Authors: Ghafoor, Umar, Ashraf, Tahreem
• Format: Article
• Language: English
• Subjects: Algorithms; Artificial Intelligence; Business and Management; Clustering; Computer Communication Networks; Downlinking; Energy efficiency; IT in Business; Linear programming; Mathematical programming; Maximization; Mixed integer; Multiple access; Networks; Nonlinear programming; Optimization; Probability Theory and Stochastic Processes; Telecommunications systems; Unmanned aerial vehicles
• ISSN: 1018-4864; 1572-9451
• DOI: 10.1007/s11235-024-01101-0

The surge in technology is driving demands for real-time interactive applications and high-speed transmissions, necessitating improved network throughput and energy efficiency (EE) for immersive experiences. The rise in industrial automation has led to higher connectivity needs, straining fifth-generation networks. Sixth-generation networks aim to address these demands, potentially maximizing throughput and EE through enhanced coverage. This paper introduces innovative techniques like phone user clustering-based downlink hybrid multiple access in unmanned aerial vehicle-assisted heterogeneous networks (HetNets) to jointly optimize phone user (PU) admission, cell association, throughput, and EE while ensuring PU fair association with cell (PUFAC) and quality of service (QoS), i.e., minimum rate requirement of PUs. An outer approximation algorithm solves the mixed integer non-linear programming (MINLP) optimization problem arising from the transformation of the concave fractional programming optimization problem using the Charnes-Cooper transformation. The method’s effectiveness is assessed, showcasing its superiority over existing macro-cell-only networks and HetNets concerning throughput, EE, PU admission, PU-cell association, PUFAC, and QoS.