LAUSR

The ambient radio frequency (RF) energy harvesting technology has recently been regarded as a potential solution for powering the wireless sensor networks (WSNs). However, the ultra-low power density of ambient RF energy is the main impediment to its further application. In this paper, we propose a novel energy efficient cooperative communication scheme (EECCS), which combines energy beamforming communication and ambient backscatter communication, to overcome the energy problem of WSNs powered by ambient RF energy harvesting. Moreover, to further reduce the energy consumption of nodes, we present an optimal resource allocation problem for EECCS. It can be formulated as a signomial geometric programming (SGP), which is nonconvex and NP-hard. We develop a Sequential Convex Approximation (SCA) algorithm for finding a solution of this SGP problem, which transforms the SGP problem into a sequence of geometric programming (GP) problems that are convex. The simulation results indicate that the EECCS can improve the energy efficiency of the ambient RF powered WSNs and maximize the total amount of data received by the sink.