Backscatter-Aided NOMA V2X Communication under Channel Estimation Errors

Backscatter communications (BC) has emerged as a promising technology for providing low-powered transmissions
in nextG (i.e., beyond 5G) wireless networks. The fundamental
idea of BC is the possibility of communications among wireless
devices by using the existing ambient radio frequency signals.
Non-orthogonal multiple access (NOMA) has recently attracted
significant attention due to its high spectral efficiency and massive
connectivity. This paper proposes a new optimization framework
to minimize total transmit power of BC-NOMA cooperative
vehicle-to-everything networks (V2XneT) while ensuring the
quality of services. More specifically, the base station (BS) transmits a superimposed signal to its associated roadside units (RSUs)
in the first time slot. Then the RSUs transmit the superimposed
signal to their serving vehicles in the second time slot exploiting
decode and forward protocol. A backscatter device (BD) in the
coverage area of RSU also receives the superimposed signal and
reflect it towards vehicles by modulating own information. Thus,
the objective is to simultaneously optimize the transmit power
of BS and RSUs along with reflection coefficient of BDs under
perfect and imperfect channel state information. The problem
of energy efficiency is formulated as non-convex and coupled
on multiple optimization variables which makes it very complex
and hard to solve. Therefore, we first transform and decouple
the original problem into two sub-problems and then employ
iterative sub-gradient method to obtain an efficient solution.
Simulation results demonstrate that the proposed BC-NOMA
V2XneT provides high energy efficiency than the conventional
NOMA V2XneT without BC.