Robust Energy-Efficient Resource Management, SIC Ordering, and Beamforming Design for MC MISO-NOMA Enabled 6G

TL;DR

This paper proposes a novel joint resource management and beamforming approach for MC MISO-NOMA 6G networks, optimizing energy efficiency through advanced non-convex optimization techniques.

Contribution

It introduces a new SIC ordering and beamforming design with a comprehensive optimization framework for energy efficiency in multi-carrier MISO-NOMA systems.

Findings

Proposed SIC ordering outperforms existing methods.

The optimization approach effectively maximizes worst-case energy efficiency.

The low-complexity alternative optimization balances performance and computational cost.

Abstract

This paper studies a novel approach for successive interference cancellation (SIC) ordering and beamforming in a multiple antennas non-orthogonal multiple access (NOMA) network with multi-carrier multi-user setup. To this end, we formulate a joint beamforming design, subcarrier allocation, user association, and SIC ordering algorithm to maximize the worst-case energy efficiency (EE). The formulated problem is a non-convex mixed integer non-linear programming (MINLP) which is generally difficult to solve. To handle it, we first adopt the linearizion technique as well as relaxing the integer variables, and then we employ the Dinkelbach algorithm to convert it into a more mathematically tractable form. The adopted non-convex optimization problem is transformed into an equivalent rank-constrained semidefinite programming (SDP) and is solved by SDP relaxation and exploiting sequential fractional programming. Furthermore, to strike a balance between complexity and performance, a low complex approach based on alternative optimization is adopted. Numerical results unveil that the proposed SIC ordering method outperforms the conventional existing works addressed in the literature.