Energy-Efficient Resource Allocation for 6G Backscatter-Enabled NOMA IoV Networks

The integration of Ambient Backscatter Communication (AmBC) with Non-Orthogonal Multiple Access (NOMA) is expected to support connectivity low-powered Internet-of-Vehicles (IoVs) in the upcoming Sixth-Generation (6G) transportation systems. This paper proposes an energy-efficient resource allocation framework for AmBC-enabled NOMA IoV network under imperfect Successive Interference Cancellation (SIC) decoding. In particular, multiple Road-Side Units (RSUs) transmit superimposed signals their associated IoVs utilizing downlink transmission. Meanwhile, Tags (BackTags) also data symbols towards nearby by reflecting RSUs. Thus, objective maximize total energy efficiency subject minimum rate all IoVs. A joint problem that simultaneously optimizes power budget each RSU, coefficient and reflection BackTags SIC decoding formulated. Dinkelbach approach first adopted transform optimization then transformed decoupled into two subproblems optimal at RSUs efficient BackTags, respectively. To solve problems efficiently, dual theory Karush-Kuhn-Tucker conditions are exploited, where Lagrangian variables iteratively calculated using subgradient method. check performance proposed framework, a benchmark without AmBC provided. Numerical results demonstrate superiority over conventional framework.