Widely Linear Processing Improves the Throughput of Nonorthogonal User Access
Year: 2025
Type: article
Abstract: The quality-of-service (QoS) provided by wireless communication networks can be upgraded by the technique of non-orthogonal multiple-access (NOMA) in tandem with widely linear beamforming (WLB), which uses a pair of beamformers for each information symbol. Conventionally, rate-fairness among the users is achieved by maximizing the users’ minimal throughput (max-min throughput optimization). However, this is computationally challenging, as each iteration requires solving a high-dimensional convex optimization problem, even for small networks. We circumvent this by maximizing the geometric mean (GM) of the users’ throughput (GM-throughput maximization) and design novel algorithms based on iterating closed-form expressions are developed, which are shown to be hundreds of times more computationally efficient than the existing algorithms that are based on convex-solvers. The proposed algorithms are developed for both conventional wireless networks and networks requiring ultra-reliable and low-latency communications (URLLC).
Authors: A. A. Nasir, H. D. Tuan, H. V. Poor, L. Hanzo
Language: English
Subfield: Electrical and Electronic Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,075
Funder: National Science Foundation
Awards: ECCS-EPSRC: NeuroComm: Brain-Inspired Wireless Communications -- From Theoretical Foundations to Implementation for 6G and Beyond, Collaborative Research: SWIFT: Nonlinear and Inseparable Radar And Data (NIRAD) Transmission Framework for Pareto Efficient Spectrum Access in Future Wireless Networks
OpenAlex ID: W4411471939
