Optimal Resource Allocation for NOMA-Assisted Backscatter Communication in 6G Internet of Vehicles Networks

Non-orthogonal multiple access (NOMA) is considered as an emerging technology to improve the spectral efficiency performance for 6G networks. Ambient backscatter communication (BackCom) is another promising solution owing to its advantages in increasing spectral and power efficiency. The investigation of integrating NOMA with BackCom is conducted to enhance the connectivity of the emerging 5G low-powered Internet-of-Vehicles (IoVs) and future 6G transportation systems. This study proposes an optimal resource allocation scheme for the NOMA-assisted BackCom IoV network. Specifically, multiple Road-Side Units (RSUs) are considered sending superimposed signals to the subscribed IoVs in the downlink NOMA. BackCom tags are considered to transmit data symbols to nearby IoVs by reflecting the signals of RSUs. Thus, we aim to maximize the total data rate performance of the NOMA-assisted BackCom IoV network. A joint problem that simultaneously optimizes the IoV clustering, IoV power allocation, and reflection coefficients of BackCom tags is formulated. To solve the problems efficiently, multiple subproblems are decomposed that can be solved using CVX optimization tool. To validate the performance of the proposed method, we compare it with those of state-of-the-art benchmark schemes. Numerical results will be provided to show the superiority of the proposed framework.