Energy-Efficient NOMA Multicasting System for 5G Cellular V2X Communications with Imperfect CSI

TL;DR

This paper proposes an energy-efficient NOMA multicasting system for 5G V2X communications that accounts for imperfect CSI, optimizing power allocation to ensure reliability and QoS under mobility-induced uncertainties.

Contribution

It introduces a roadside unit assisted NOMA multicasting system with novel power allocation algorithms tailored for imperfect CSI in high-mobility vehicular networks.

Findings

Efficient power allocation algorithms under outage probability constraints.

Successful conversion of probabilistic optimization to deterministic form.

Enhanced energy efficiency in V2X communications with imperfect CSI.

Abstract

Vehicle-to-everything (V2X) is a modern vehicular technology that improves conventional vehicle systems in traffic and communications. V2X communications demand energyefficient and high-reliability networking because of massive vehicular connections and high mobility wireless channels. Nonorthogonal multiple access (NOMA) is a promising solution for 5G V2X services that intend to guarantee high reliability, quality-of-service (QoS) provisioning, and massive connectivity requirements. In V2X, it is vital to inspect imperfect CSI because the high mobility of vehicles leads to more channel estimation uncertainties. Unlike existing literatures, we propose energy-efficient roadside units (RSUs) assisted NOMA multicasting system for 5G cellular V2X communications, and investigate the energy-efficient power allocation problem. The proposed system multicast the information through low complexity optimal power allocation algorithms used under channel outage probability constraint of vehicles with imperfect CSI, QoS constraints of vehicles, and transmit power limits constraint of RSUs. The formulated problem with the channel outage probability constraint is a nonconvex probabilistic optimization problem. This problem is solved efficiently by converting the probabilistic problem through relaxation into a non-probabilistic problem.