QoE-Oriented Resource Allocation for Downlink Non-Orthogonal Multiple Access

In this letter, we investigate the resource allocation problem, including user pairing and power allocation, for downlink non-orthogonal multiple access (NOMA) networks. Different from most of the existing studies focusing on maximizing throughput, we aim to maximize users' quality-of-experience (QoE) considering demand diversity. We apply mean opinion score (MOS) to evaluate user's QoE level, and the optimization target is to maximize the sum MOSs of all users, which is a complex non-convex problem. To tackle this problem, we firstly propose a linear searching algorithm to get the optimal sum MOSs for a specific 2-user NOMA system. Then, we derive the corresponding power allocation strategy. Furthermore, we extend it to a general NOMA system with 2K users, and design a fast and low complexity scheme. Results show that our proposed scheme can significantly improve the users' sum MOSs in the NOMA networks, compared with other existing schemes.