Energy-efficient joint resource allocation for heterogeneous cellular networks with wireless backhauls

The extensive utilization of wireless services, coupled with the exponential surge in data traffic, has triggered substantial energy consumption. Thereby, growing attentions have been paid to energy-efficient heterogeneous cellular networks (HCNs). In this paper, we concentrate on the joint resource allocation issue under the framework of the non-orthogonal multiple access (NOMA) assisted HCNs with wireless backhauls. To furthermore improve the total system energy efficiency (EE) while ensuring the quality of service (QoS), we formulate the optimization problem as a hybrid joint resource allocation (HJRA) of integer programming and continuous optimization under the cross-tier interference threshold and minimum data rate constraint. The non-convex nature of the optimization problem arises from the fractional objective function and non-convex constraints, making it intractable to efficiently get an exact solution. In this regard, a quantum-inspired political optimizer (QPO) algorithm is devised to find the optimal solution for the HJRA issue, which realizes synchronous allocation of backhaul bandwidth, sub-channels, and power. Simulation results confirm the superiority of the QPO regarding the total system EE over other strategies.