Optimum Power-Subcarrier Allocation and Time-Sharing in Multicarrier NOMA Uplink
Sagnik Bhattacharya, Kamyar Rajabalifardi, Muhammad Ahmed Mohsin, John M. Cioffi
TL;DR
This work tackles uplink MC-NOMA resource allocation by decoupling power-subcarrier allocation from the SIC decoding order and solving a convex optimization for the former. It then derives the optimal decoding order via dual variables, ensuring a consistent order across all subcarriers, and introduces a time-sharing mechanism to combine multiple orders when a single order cannot meet rate targets, minimizing latency. The combined approach yields higher sum rates and lower power consumption than OMA, NOMA, and prior MC-NOMA methods, with gains most pronounced at higher SNRs. Practically, the framework enables scalable, low-latency uplink MC-NOMA deployments that approach the information-theoretic limits while satisfying per-user rate requirements; key metrics are denoted by $R_{\text{sum}}$ and $P_{\text{tot}}$.
Abstract
Currently used resource allocation methods for uplink multicarrier non-orthogonal multiple access (MC-NOMA) systems have multiple shortcomings. Current approaches either allocate the same power across all subcarriers to a user, or use heuristic-based near-far, strong channel-weak channel user grouping to assign the decoding order for successive interference cancellation (SIC). This paper proposes a novel optimal power-subcarrier allocation for uplink MC-NOMA. This new allocation achieves the optimal power-subcarrier allocation as well as the optimal SIC decoding order. Furthermore, the proposed method includes a time-sharing algorithm that dynamically alters the decoding orders of the participating users to achieve the required data rates, even in cases where any single decoding order fails to do so. Extensive experimental evaluations show that the new method achieves higher sum data rates and lower power consumption compared to current NOMA methods.