Joint Decoding Order and Power Optimization for Sum-Rate and Fairness Maximization in NOMA

Non-orthogonal multiple access (NOMA) offers a promising solution to enhance spectral efficiency and support massive connectivity in future wireless systems. However, most NOMA research assumes ideal conditions, neglecting the impact of imperfect successive interference cancellation (SIC) and relying on conventional decoding order based on channel gains. In this work, we address these limitations by considering all possible decoding order combinations for a two-user NOMA system and developing a systematic approach for joint optimization of decoding order and power allocation. Our goal is to maximize the sum-rate and fairness under realistic conditions, including imperfect SIC. We formulate a joint optimization problem to maximize sum-rate while ensuring each user's data rate meets a minimum quality-of-service (QoS) requirement, and tackle the max-min fairness problem to ensure fairness. The optimal decoding order is proven analytically, and global optimal power allocation solutions are derived. Extensive simulations validate our theoretical results, showing that the proposed scheme outperforms conventional methods in sum-rate and fairness.