Energy Minimization for IRS-Aided WPCNs With Non-Linear Energy Harvesting Model

This letter considers an intelligent reflecting surface(IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy from a power station (PS) in the downlink (DL) and then transmit information using non-orthogonal multiple access (NOMA) to a data sink in the uplink (...

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Published in:IEEE wireless communications letters Vol. 10; no. 11; pp. 2592 - 2596
Main Authors: Zeng, Piao, Wu, Qingqing, Qiao, Deli
Format: Journal Article
Language:English
Published: Piscataway IEEE 01.11.2021
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Array signal processing
Beamforming
dynamic beamforming
Energy consumption
Energy harvesting
IRS
Mathematical analysis
NOMA
non-linear energy harvesting
Nonorthogonal multiple access
Optimization
Power plants
Quality of service
Resource allocation
Resource management
Throughput
Wireless communication
Wireless communications
WPCN
ISSN:2162-2337, 2162-2345
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Abstract This letter considers an intelligent reflecting surface(IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy from a power station (PS) in the downlink (DL) and then transmit information using non-orthogonal multiple access (NOMA) to a data sink in the uplink (UL). However, most existing works on WPCNs adopted the simplified linear energy-harvesting model and also cannot guarantee strict user quality-of-service requirements. To address these issues, we aim to minimize the total transmit energy consumption at the PS by jointly optimizing the resource allocation and IRS phase shifts over time, subject to the minimum throughput requirements of all devices. The formulated problem is decomposed into two subproblems, and solved iteratively in an alternative manner by employing difference of convex functions programming, successive convex approximation, and penalty-based algorithm. Numerical results demonstrate the significant performance gains achieved by the proposed algorithm over benchmark schemes and reveal the benefits of integrating IRS into WPCNs. In particular, employing different IRS phase shifts over UL and DL outperforms the case with static IRS beamforming.
AbstractList This letter considers an intelligent reflecting surface(IRS)-aided wireless powered communication network (WPCN), where devices first harvest energy from a power station (PS) in the downlink (DL) and then transmit information using non-orthogonal multiple access (NOMA) to a data sink in the uplink (UL). However, most existing works on WPCNs adopted the simplified linear energy-harvesting model and also cannot guarantee strict user quality-of-service requirements. To address these issues, we aim to minimize the total transmit energy consumption at the PS by jointly optimizing the resource allocation and IRS phase shifts over time, subject to the minimum throughput requirements of all devices. The formulated problem is decomposed into two subproblems, and solved iteratively in an alternative manner by employing difference of convex functions programming, successive convex approximation, and penalty-based algorithm. Numerical results demonstrate the significant performance gains achieved by the proposed algorithm over benchmark schemes and reveal the benefits of integrating IRS into WPCNs. In particular, employing different IRS phase shifts over UL and DL outperforms the case with static IRS beamforming.
Author Qiao, Deli
Wu, Qingqing
Zeng, Piao
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SubjectTerms Algorithms
Array signal processing
Beamforming
dynamic beamforming
Energy consumption
Energy harvesting
IRS
Mathematical analysis
NOMA
non-linear energy harvesting
Nonorthogonal multiple access
Optimization
Power plants
Quality of service
Resource allocation
Resource management
Throughput
Wireless communication
Wireless communications
WPCN
Title Energy Minimization for IRS-Aided WPCNs With Non-Linear Energy Harvesting Model
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https://www.proquest.com/docview/2595718413
Volume 10
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