Energy Efficiency Maximization for Downlink NOMA Designs via Symbol-Level Precoding

The multi-antenna non-orthogonal multiple access (NOMA) technique is a promising method to enhance energy and spectrum efficiencies of wireless communication systems through advanced precoding algorithms. However, conventional NOMA schemes encounter high complexity issues due to the successive interference cancellation (SIC) process at the receiver end. Moreover, traditional precoding designs for multi-antenna NOMA systems only utilize user channel state information and overlook the modulation details of transmitted data symbols, which may result in suboptimal performance. To overcome these disadvantages, we propose a symbol-level precoding (SLP) scheme to maximize the energy efficiency of the downlink NOMA systems. In particular, by the proposed SLP scheme, the “interference signals” is designed to fall within the decoding region of the “desired signal”, eliminating the need for an SIC receiver, thereby reducing the complexity of the NOMA system in practical applications. For ease of illustrating the idea of the SLP-based NOMA designs, we first focus on a single user group case with two users, and solve the associated problem by developing a fractional programming-based algorithm. Then, we extend the idea to the multi-user scenarios and focus on the joint user grouping and SLP design. For the purpose of computational complexity reduction, a low-complexity (adaptive) user grouping scheme is proposed based on the idea of unsupervised clustering. Finally, numerical simulations are carried out to validate the effectiveness of the proposed SLP scheme and algorithms in improving the energy efficiency of the system.