Energy-Efficient Analog Beamforming for RF-WET with Charging Time Constraint
Internet of Things (IoT) sustainability may hinge on radio frequency wireless energy transfer (RF-WET). However, energy-efficient charging strategies are still needed, motivating our work. Specifically, this letter proposes a time division scheme to efficiently charge low-power devices in an IoT network. For this, a multi-antenna power beacon (PB) drives the devices' energy harvesting circuit to the highest power conversion efficiency point via energy beamforming, thus achieving minimum energy consumption. Herein, we adopt the analog multi-antenna architecture due to its low complexity, cost, and energy consumption. The proposal includes a simple yet accurate model for the transfer characteristic of the energy harvesting circuit, enabling the optimization framework. The results evince the effectiveness of our RF-WET strategy over a benchmark scheme where the PB charges all the IoT devices simultaneously. Furthermore, the performance increases with the number of PB antennas.
Code (1)
Similar Papers 제목 키워드 기반
On-Request Wireless Charging and Partial Computation Offloading In Multi-Access Edge Computing Systems
Wireless charging coupled with computation offloading in edge networks offers a promising solution for realizing power-hungry and computation intensive applications on user devices. We consider a multi-access edge comput…
Edge-computingEnergy-efficient Wireless Charging and Computation Offloading In MEC Systems
Wireless charging coupled with computation offloading in edge networks offers a promising solution for realizing power-hungry and computation intensive applications on user devices. We consider a mutil-access edge comput…
Edge-computingSystem Energy-Efficient Hybrid Beamforming for mmWave Multi-user Systems
This paper develops energy-efficient hybrid beamforming designs for mmWave multi-user systems where analog precoding is realized by switches and phase shifters such that radio frequency (RF) chain to transmit antenna con…
compressed sensingFormEnd-to-End Waveform and Beamforming Optimization for RF Wireless Power Transfer
Radio frequency (RF) wireless power transfer (WPT) is a key technology for future low-power wireless systems. However, the inherently low end-to-end power transfer efficiency (PTE) is challenging for practical applicatio…
Deep Reinforcement Learning for Multi-User RF Charging with Non-linear Energy Harvesters
Radio frequency (RF) wireless power transfer (WPT) is a promising technology for sustainable support of massive Internet of Things (IoT). However, RF-WPT systems are characterized by low efficiency due to channel attenua…
Deep Reinforcement LearningScheduling