Adaptive Overhead-to-Throughput Ratio Thresholding with Convergence Guarantees for Energy-Efficient Resource Allocation in Beyond 5G Heterogeneous Network

Bright Agbonze, M. D. Almustapha, Surajo Muhammad, Ezekiel Egbon, Ndifreke Bassey, Elvis Obi, S. A. Mikail

Abstract


Beyond 5G (B5G) Heterogeneous Networks (HetNets) demand scalable, energy-efficient resource allocation methods that reduce signalling overhead while sustaining high performance. This study proposes a Signal Overhead-Aware Hybrid Non-Orthogonal Multiple Access (SOA-H-NOMA) algorithm that introduces the Overhead-to-Throughput Ratio (OTR) as a novel optimization constraint for adaptive clustering, base station association, and power allocation. The algorithm was implemented in MATLAB and benchmarked against the conventional Energy-Efficient Resource Allocation (EERA) scheme. Results show that SOA-H-NOMA achieved substantial throughput gains, with 54.71% improvement in Macro Base Station (MBS)-only networks (2-23 Mbps to 3-25 Mbps) and 39.80% in HetNets (3-28 Mbps to 4-36 Mbps). Energy efficiency (EE) also improved by 76.27% in MBS-only networks and 53.88% in HetNets, alongside a 21.8% reduction in clustering delay. Notably, this study uniquely reports improvements in UE admission rates, with increases of 36.65% in MBS-only networks (4-43 to 6-58) and 15.73% in HetNet scenarios (7-60 to 9-65). Further evaluation confirms consistent performance across EE distribution versus number of UEs and throughput/EE trade-offs under varying required rates, demonstrating robustness under dynamic traffic conditions. Overall, the findings establish SOA-H-NOMA as an adaptive and energy-conscious framework that jointly optimizes throughput, energy efficiency, user admission, and signalling overhead, providing a scalable solution for next-generation wireless networks.


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References


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