Energy-Efficient Resource Allocation for Wirelessly Powered Backscatter Communications

Abstract

In this letter we consider a wireless-powered backscatter communication (WP-BackCom) network, where the transmitter first harvests energy from a dedicated energy RF 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. The 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.

A Prospective Look: Key Enabling Technologies, Applications and Open Research Topics in 6G Networks

“…In addition to the aforementioned studies, major research efforts have focused on channel modeling and estimation [261]- [266], resource allocation [252], [253], [267]- [269] and wireless energy harvesting [270]- [276] in BackCom systems. Table 8 summarizes the timely open research topics in the field of BackCom.…”

Max-Min Energy-Efficient Resource Allocation for Wireless Powered Backscatter Networks

“…In recent years, throughput maximization [2], signal detection [3] and hardware implementation [4] have been investigated for wireless powered backscatter communications, but the energy efficiency (EE) problem has not been sufficiently studied. The authors in [5] maximized the EE of a backscatter link by jointly optimizing the reflection coefficient and the power beacon (PB) transmission power. The EE maximization problem was studied for radio frequency (RF) powered cognitive backscatter communications [6].…”

“…The EE maximization problem was studied for radio frequency (RF) powered cognitive backscatter communications [6]. However, both [5] and [6] considered only a single backscatter link and their results cannot be readily applied to multiple co-channel wireless powered backscatter links. Moreover, when multiple backscatter transmitters share the transmission power from a PB, it is necessary to ensure the fairness among the co-channel backscatter links.…”

Max-Min Throughput in Hybrid of Wireless Powered NOMA and Backscatter Communications

“…In order to harvest sufficient energy for active transmissions, the transmitter, in WPCNs, should allocate a long period within the time block for EH, leaving a short period within the time block for active transmissions, and this limits the its achievable throughput. Different from the WPCN, in BackComs, the transmitter splits the incoming signal transmitted by a carrier emitter into two parts based on a reflection coefficient: one is used as a carrier signal for modulating its own message and then is backscattered towards its associated receiver, and the other is fed into the energy harvester for EH so as to operate its circuit [11], [13]. Accordingly, the transmitter in BackComs bypasses the need of energy-consuming active components for generating carrier signals and BackCom is recognized as an ultra low-power communication technology.…”

“…Author et al: Preparation of Papers for IEEE TRANSACTIONS and JOURNALS (13). Note that the iteration to update α k and µ k always converges and the equality in (11) holds at the converged solution. The detailed proof can be refer to [31].…”