Maximizing Energy Efficiency in Downlink Cooperative SWIPT-NOMA Networks

Simultaneous Wireless Information and Power Transfer (SWIPT) integrated with non-orthogonal multiple access (NOMA) offers a promising solution for energy-efficient Internet of Things (IoT) applications in the context of increasingly scarce spectrum resources. This paper addresses the energy efficiency (EE) maximization problem in a downlink cooperative SWIPT-NOMA network, where user cooperation is employed to mitigate the near-far effect and enhance network performance. We formulate the EE optimization problem for a multi-user scenario by jointly optimizing the transmission time, the power allocation ratio, and the transmission power of the near user in the cooperative SWIPT-NOMA network, and we propose a cooperative SWIPT-NOMA energy efficiency allocation algorithm. Firstly, the fractional programming problem for EE maximization is transformed into a more tractable form using the Dinkelbach method. Subsequently, the resource allocation variables are iteratively updated via variable substitution, successive convex approximation, and the Lagrangian dual method until the algorithm converges. Extensive simulations are conducted to evaluate the performance of the proposed algorithm under various conditions and to compare it with existing schemes. The proposed algorithm enhances network energy efficiency while ensuring user throughput, providing a more efficient resource allocation solution for wireless communication networks.