Optimal and Near-Optimal Policies for Wireless Power Transfer Considering Fairness

Rezaei, Roohollah; Movahednasab, Mohammad; Omidvar, Naeimeh; Pakravan, Mohammad Reza

doi:10.1109/glocom.2018.8648052

Cited by 9 publications

(2 citation statements)

References 28 publications

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“…2 P 2 peak , and (a) results from the virtual queue update equation (line 11 of Algorithm 1). The transmitted signal at the E-AP has a maximum power of P peak , so 1 2…”

Section: Appendix B Proof Of Theoremmentioning

confidence: 99%

“…In some other applications such as medical implants inside human bodies, replacement of the batteries is highly difficult and almost impractical. To address the issues mentioned above, wireless power transfer (WPT) is proposed as a key enabling technology to provide Part of this work has been presented in IEEE Global Communications Conference (GLOBECOM) 2018 [1]. The first author acknowledges the support of the Agency for Science, Technology and Research (A*STAR) Research Attachment Program (ARAP).…”

Section: Introductionmentioning

confidence: 99%

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Efficient, Fair and QoS-Aware Policies for Wirelessly Powered Communication Networks

Rezaei¹,

Omidvar²,

Movahednasab³

et al. 2019

Preprint

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Wireless power transfer (WPT) is a viable source of energy for wirelessly powered communication networks (WPCNs). In this paper, we first consider WPT from an energy access point (E-AP) to multiple energy receivers (E-Rs) to obtain the optimal policy that maximizes the WPT efficiency. For this purpose, we formulate the problem of maximizing the total average received power of the E-Rs subject to the average and peak power level constraints of the E-AP. The formulated problem is a non-convex stochastic optimization problem. Using some stochastic optimization techniques, we tackle the challenges of this problem and derive a closed-form expression for the optimal solution, which requires the explicit knowledge of the distribution of channel state information (CSI) in the network. We then propose a near-optimal algorithm that does not require any explicit knowledge of the CSI distribution and prove that the proposed algorithm attains a near-optimal solution within a guaranteed gap to the optimal solution. We next consider fairness among the E-Rs and propose a quality of service (QoS) aware fair policy that maximizes a generic network utility function while guaranteeing the required QoS of each E-R. Finally, we study a practical wirelessly powered communication scenario in which the E-Rs utilize their energy harvested through WPT to transmit information to the E-AP. We optimize the received information at the E-AP under its average and peak transmission power constraints and the fairness constraints of the E-Rs. Numerical results show the significant performance of our proposed solutions compared to the state-of-the-art baselines.

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“…2 P 2 peak , and (a) results from the virtual queue update equation (line 11 of Algorithm 1). The transmitted signal at the E-AP has a maximum power of P peak , so 1 2…”

Section: Appendix B Proof Of Theoremmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Efficient, Fair and QoS-Aware Policies for Wirelessly Powered Communication Networks

Rezaei¹,

Omidvar²,

Movahednasab³

et al. 2019

Preprint

Self Cite

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Time Division Wireless Power Transfer Using Receiver Grouping

Sawada,

Shiraki,

Matsuda

et al. 2024

IEEE Access

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Joint Data Routing and Power Scheduling for Wireless Powered Communication Networks

Movahednasab

Omidvar

Pakravan

et al. 2019

ICC 2019 - 2019 IEEE International Conference on Communications (ICC)

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In a wireless powered communication network (WPCN), an energy access point supplies the energy needs of the network nodes through radio frequency wave transmission, and the nodes store the received energy in their batteries for their future data transmission. In this paper, we propose an online stochastic policy that jointly controls energy transmission from the EAP to the nodes and data transfer among the nodes. For this purpose, we first introduce a novel perturbed Lyapunov function to address the limitations on the energy consumption of the nodes imposed by their batteries. Then, using Lyapunov optimization method, we propose a policy which is adaptive to any arbitrary channel statistics in the network. Finally, we provide theoretical analysis for the performance of the proposed policy and show that it stabilizes the network, and the average power consumption of the network under this policy is within a bounded gap of the minimum power level required for stabilizing the network. battery disposal. Wireless Power Transfer (WPT) is the key enabling technology for charging over the air. There are various WPT methods including Radio Frequency (RF) power transfer [3], resonant coupling [4] and inductive coupling [5]. Compared to the two latter methods, RF power transfer provides a wider coverage range and is more flexible for transmitter/receiver deployment and movement [2]. Therefore, it is considered as the most promising WPT approach by the literature. Adapting WPT technology in wireless communication networks introduces new research challenges, mostly related to increasing coverage and efficiency. A prominent challenge is how to maintain power transfer efficiency despite the transmission path loss [6]. There has been numerous studies on energy beamforming as a technique for alleviating the high transmission path loss (e.g., see [6]-[9]). In [6] and [7], a wireless powered communication network (WPCN) consisting of a hybrid data/energy access point with multiple antennas and several single-antenna users is considered, in which the access point transmits energy toward the nodes in the down-link direction and November 27, 2018 DRAFT

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Optimal and Near-Optimal Policies for Wireless Power Transfer Considering Fairness

Cited by 9 publications

References 28 publications

Efficient, Fair and QoS-Aware Policies for Wirelessly Powered Communication Networks

Efficient, Fair and QoS-Aware Policies for Wirelessly Powered Communication Networks

Time Division Wireless Power Transfer Using Receiver Grouping

Joint Data Routing and Power Scheduling for Wireless Powered Communication Networks

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