Joint resource allocation for QoE optimization in large-scale NOMA-enabled multi-cell networks

The non-orthogonal multiple access (NOMA) technology has been considered as a promising technology for the upcoming six-generation mobile communication networks (6G). However, with the increasing complexity of this access technology, how to allocate the limited network resources effectively for massive number of connectivity becomes more and more challenging. The QoE optimization problem including both the sub-channel (SC) assignment and power allocation is formulated. In order to cope with it, we first decouple it into two sub-problems: the UE-BS association, SC assignment sub-problem and the power allocation sub-problem. We thus propose genetic algorithm (GA) for UE-BS association, SC assignment and artificial bee colony (ABC) algorithm for power allocation. The corresponding constraints satisfying mechanisms are also proposed to ensure the feasibility of individual bee colony in each iteration, thus to accelerate the convergence. The simulation results show that the proposed power allocation scheme can converge to the optimal solution quickly, and the MOS can be increased by increasing the number of users (UE), and SCs.