Energy-Efficient Resource Allocation for Wirelessly Powered Backscatter Communications

TLDR

The letter studies a wireless‑powered backscatter communication network in which the transmitter first harvests energy from a dedicated RF source while in sleep mode. The authors aim to maximize energy efficiency by jointly optimizing time allocation, reflection coefficient, and source transmit power, despite the problem’s non‑convexity. They model simultaneous backscattering and energy harvesting via a reflection coefficient and solve the resulting non‑convex optimization with a Dinkelbach‑based iterative algorithm. Each iteration shows that the energy‑efficient network is equivalent to either a fully active transmitter or a source operating at maximum power.

Abstract

In this letter, we consider a wireless-powered backscatter communication (WP-BackCom) network, where the transmitter first harvests energy from a dedicated RF energy source (S) in the sleep state. It subsequently backscatters information and harvests energy simultaneously through a reflection coefficient. Our goal is to maximize the achievable energy efficiency of the WP-BackCom network via jointly optimizing time allocation, reflection coefficient, and transmit power of S. The optimization problem is non-convex and challenging to solve. We develop an efficient Dinkelbach-based iterative algorithm to obtain the optimal resource allocation scheme. This study shows that for each iteration, the energy-efficient WP-BackCom network is equivalent to either the network in which the transmitter always operates in the active state, or the network in which S adopts the maximum allowed power.