Optimized Scheduling and Beamforming for Enhanced Efficiency in Wireless-Powered IoT Networks

Wireless-powered communication networks (WPCNs) have emerged as a vital technology for enabling sustainable Internet of Things (IoT) systems, particularly in the context of the forthcoming 6G era. WPCNs offer a promising solution to the challenge of powering a large number of energy-constrained IoT devices (IoTDs) by wirelessly transmitting energy while concurrently managing data communications. However, optimizing energy efficiency (EE) in the downlink and information efficiency (IE) in the uplink remains a critical challenge in these networks. In this article, we propose a novel scheduling framework to optimize EE in the downlink and IE in the uplink of a WPCN with a hybrid access point (H-AP) and multiple IoTDs. Our approach reduces beamforming complexity by grouping devices based on location for wireless energy transfer (WET) and introduces a location-aware scheduling method for wireless information transfer (WIT) that minimizes interference using a hybrid NOMA-TDMA scheme. We also optimize time allocations between WET and WIT to enhance the overall system efficiency. Simulation results demonstrate the superior performance of our framework, significantly improving both EE and IE compared to existing methods.

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Publication Details

Journal
IEEE Sensors Journal
Published
2024-12-31
DOI
https://doi.org/10.1109/jsen.2024.3521452
Citations
1
Primary Topic
Energy Harvesting in Wireless Networks
Type
article
Field-Weighted Citation Impact
0.21

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article

Optimized Scheduling and Beamforming for Enhanced Efficiency in Wireless-Powered IoT Networks

Igbafe Orikumhi, Hyoung‐Kyu Song, Iqra Hameed, Sunwoo Kim
1 citations
IEEE Sensors Journal
Energy Harvesting in Wireless Networks
0.21
article

Optimized Scheduling and Beamforming for Enhanced Efficiency in Wireless-Powered IoT Networks

Igbafe Orikumhi, Hyoung‐Kyu Song, Iqra Hameed, Sunwoo Kim
article en
1 citations

Abstract

Wireless-powered communication networks (WPCNs) have emerged as a vital technology for enabling sustainable Internet of Things (IoT) systems, particularly in the context of the forthcoming 6G era. WPCNs offer a promising solution to the challenge of powering a large number of energy-constrained IoT devices (IoTDs) by wirelessly transmitting energy while concurrently managing data communications. However, optimizing energy efficiency (EE) in the downlink and information efficiency (IE) in the uplink remains a critical challenge in these networks. In this article, we propose a novel scheduling framework to optimize EE in the downlink and IE in the uplink of a WPCN with a hybrid access point (H-AP) and multiple IoTDs. Our approach reduces beamforming complexity by grouping devices based on location for wireless energy transfer (WET) and introduces a location-aware scheduling method for wireless information transfer (WIT) that minimizes interference using a hybrid NOMA-TDMA scheme. We also optimize time allocations between WET and WIT to enhance the overall system efficiency. Simulation results demonstrate the superior performance of our framework, significantly improving both EE and IE compared to existing methods.

IEEE Sensors JournalVol. 25(4)
Sejong University (KR), Hanyang University (KR)
National Research Foundation of Korea, Institute for Information and Communications Technology Promotion
Affordable and clean energy
Openalex Percentile: Top 44%
Energy Harvesting in Wireless Networks
0.21
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