Dynamic Power Allocation For NOMA-Based Transmission in 6G Optical Wireless Networks

TL;DR

This paper proposes a dynamic power allocation method for NOMA-based optical wireless networks in 6G, optimizing group formation and power distribution to maximize sum rate and fairness.

Contribution

It introduces a novel dynamic NOMA application with algorithms for user grouping and power allocation, enhancing spectral efficiency and system performance in optical wireless communications.

Findings

Converges to optimal solutions in simulations.

Achieves higher sum rate and fairness.

Improves energy efficiency compared to existing schemes.

Abstract

OWC has been considered as a key enabling technology to unlock unprecedented speeds of communication, supporting high demands of data traffic. In this paper, infrared lasers are used as optical transmitters operating in an indoor environment under eye safety regulations due to their high modulation speed. To provide efficient multiple access service, NOMA-based transmission is implemented to multiplex messages intended to multiple users in the power domain and maximize the spectral efficiency of our laser-based OWC network. In particular, a BIA outer precoder is designed to coordinate the transmission among multiple APs and determine the precoding matrices for groups of users potential formed according to NOMA principles. For effective use of NOMA, an optimization problem is formulated to maximize the sum rate of the network through forming optimum groups under certain joint conditions, efficient power allocation, high quality of service for each weak and strong users, and high overall system performance. Such optimization problems are defined as max-min fractional programs difficult to solve in practice. Therefore, a dynamic application for NOMA is introduced using two algorithms. First, a RF-aided dynamic algorithm is designed to form multiple groups, where users exchange binary variables among them through an RF system to establish distance-based weight edges, which are used as a metric for the grouping process. Second, a dynamic power allocation is proposed to determine the optimum power allocated to each group, while the users belonging to a certain group receive their traffic demands regardless of their classification as weak or strong. The results show the convergence of the proposed dynamic application to the optimum solution, and its high performance in terms of sum rate, fairness, and energy efficiency compared to counterpart schemes.