Uplink NOMA systems: The power allocation method for improving the tradeoff between spectral efficiency and energy performance

NOMA that means Non-Orthogonal Multiple Access is technique which considered promising for next-generation communication systems due to its high spectrum efficiency. In the uplink architectures based on NOMA, an optimization issue for maximizing the possible sum rate while ensuring users’ Quality of Service (QoS) and restricting total power is addressed. This study proposes an energy allocation strategy utilizing a genetic algorithm (GA) to handle the nonlinear power allocation problem. By employing various target functions and optimization criteria, multiple power allocation coefficients can be generated. The focus is on maximizing the SE-EE (Spectral Efficiency and Energy Efficiency) tradeoff for multi clusters, multi-user applications in systems. In this work, the power allocation optimization considers each user’s minimum rate requirements and power budget. The subsequent analysis aims to optimize each cluster’s SE-EE tradeoff. Simulation outcomes demonstrate that our proposed strategy outperforms previous solutions in terms of the SE-EE tradeoff.