Abstract
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.
Highlights
The sensor nodes in wireless sensor networks (WSNs) use finite energy sources
To satisfy the requirements of extremely low energy consumption of sensor nodes in ambient RF-powered WSNs, we propose an energy efficient cooperative communication scheme (EECCS), which combines energy beamforming and ambient backscattering
The simulation results are provided to show the performance of the energy efficient cooperative communication scheme and verify the feasibility and effectiveness of Sequential Convex Approximation (SCA) algorithm
Summary
The sensor nodes in wireless sensor networks (WSNs) use finite energy sources (e.g., batteries). The energy constraints of these energy sources constitute a major impediment to the application and generalization of WSNs. Recent advances in ambient energy (e.g., solar, thermal and wind) harvesting technology have made it possible for sensor nodes to be powered by ambient energy instead of batteries [1]. Based on ambient energy harvesting technology, WSNs can operate perpetually and are economical in the long-term because ambient energy can be harvested from the environment perpetually. Among the multiple ambient energy sources, the radio-frequency (RF) energy-harvesting technology has dramatically grown recently due to the growing ubiquity of wireless signals, such as TV, cellular, and WiFi signals.
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