  This work presents non-orthogonal multiple access (NOMA) enabled
energy-efficient alternating optimization framework for backscatter aided
wireless powered uplink sensors communications for beyond 5G intelligent
transportation system (ITS). Specifically, the transmit power of carrier
emitter (CE) and reflection coefficients of backscatter aided roadside sensors
are optimized with channel uncertainties for the maximization of the energy
efficiency (EE) of the network. The formulated problem is tackled by the
proposed two-stage alternating optimization algorithm named AOBWS (alternating
optimization for backscatter aided wireless powered sensors). In the first
stage, AOBWS employs an iterative algorithm to obtain optimal CE transmit power
through simplified closed-form computed through Cardano's formulae. In the
second stage, AOBWS uses a non-iterative algorithm that provides a closed-form
expression for the computation of optimal reflection coefficient for roadside
sensors under their quality of service (QoS) and a circuit power constraint.
The global optimal exhaustive search (ES) algorithm is used as a benchmark.
Simulation results demonstrate that the AOBWS algorithm can achieve
near-optimal performance with very low complexity, which makes it suitable for
practical implementations.
