Optimisation of energy efficiency of ambient backscatter communication and reconfigurable intelligent surfaces in non-orthogonal multiple access downlink

The authors study the energy efficiency (EE) of ambient backscatter communication (AmBC) device-assisted and reconfigurable intelligent surfaces (RIS)-assisted non-orthogonal multiple access (NOMA) downlinks. The authors establish two optimisation problems based on the two collaborative devices (AmBC devices, RIS) with the objective of maximising the EE of the system, taking into account the requirements of power limitation and rate limitation, etc. and also obtain the solutions of two problems by optimising the relevant performance metrics based on the alternating optimisation algorithm. For the backscatter device (BD)-aided downlink NOMA network, the problem is first decoupled into three subproblems, where the power allocation optimisation subproblem is solved by using the quadratic transformation method and the subgradient algorithm. The maximum EE is obtained by iterating according to the Dinkelbach's algorithm. For the RIS-aided downlink NOMA network, the power allocation problem is solved by the same method as above and the phase optimisation problem is solved by the successive convex approximation method. Numerical results show that the proposed algorithm can achieve convergence after several iterations, and the EE of systems with BD-assisted and RIS-assisted have different levels of sensitivity to different influencing factors. The authors study the resource allocation problem of non-orthogonal multiple access (NOMA) downlink in Internet of Things (IoT) environment combined with the Ambient Backscatter Communication (AmBC) and the reconfigurable intelligent surface (RIS). Aiming to maximise the system energy efficiency, and considering the power limitation, rate limitation and other requirements, the solution is obtained by jointly optimising the relevant performance metrics based on the alternating optimisation (AO) algorithm. image