Publication | Closed Access
Energy Efficiency Optimization in SWIPT Enabled WSNs for Smart Agriculture
85
Citations
35
References
2020
Year
Precision AgricultureEngineeringWireless Sensor SystemEnergy EfficiencyAgricultural EconomicsEnergy Efficiency OptimizationGreen CommunicationsGreen NetworkingSmart Wireless NetworkSensor NetworksSystems EngineeringInternet Of ThingsGreen Communication SystemSmart AgricultureRelay SensorEnergy HarvestingGreen CommunicationDestination SensorEnergy ManagementEnergy IotTechnologyEnergy-efficient Networking
Smart agriculture is able to optimize the information resources of agriculture, which can improve the quality and productivity of agricultural products. Wireless sensor networks (WSNs) provide smart agriculture with effective solutions for collecting, transmitting, and processing of information. However, the large number of sensor networks consume too much energy that violates the principle of green communication. Simultaneous wireless information and power transfer (SWIPT) technology utilizes radio-frequency signals to transmit information and provide energy to WSNs, which can extend the lifetime of WSNs effectively. In this article, an architecture design of smart agriculture is first proposed by exploiting the SWIPT. Then, an energy efficiency optimization scheme is studied to achieve green communication, in which the subcarriers' pairing and power allocation are jointly optimized. The process of communication is divided into two phases. Specifically, in the first phase, source sensor sends information to relay sensor and destination sensor. Relay sensor utilizes a part of the subcarriers to receive the information, and utilizes the remaining subcarriers to collect energy. Destination sensor uses all the subcarriers to receive the information. In the second phase, relay sensor utilizes the energy collected in the first phase to forward the information to destination sensor. An effective iterative optimization algorithm is proposed to resolve the proposed optimization problem through Lagrangian dual function. Simulation results validate that the performance of the algorithm can improve energy efficiency of the system effectively.
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