IRS-assisted cooperative offloading in integrated wireless power transfer and mobile edge computation system

The intelligent reflecting surface (IRS) can intelligently control the wireless communication environment to improve communication quality and wireless power transfer (WPT) technology enables wireless devices powered over the air by dedicated wireless power transmitters for communications. Hence, the integration of IRS and WPT is a promising technology to provide sustainable energy supply and improve computing service in mobile edge computing (MEC) system. Inspired by this, we consider an IRS assisted wireless power transfer-mobile edge computing (WPT-MEC) system, where a hybrid access point (HAP) with server is deployed to charge the low-power wireless devices for sustainable energy supply by the radio-frequency (RF) signal. And the cooperative offloading scheme is adopted in such a system to improve the computation performance of wireless devices, in which the surrounding near devices with idle computation resource are enabled as helpers to use the harvested energy help far device execute computing tasks. All the devices are subject to the energy balance constraints, thus their energy consumption does not exceed the harvested energy from HAP. Under above setup, we maximize the total computation bits for all devices by jointly optimizing the time allocation, power allocation, local computing capability and IRS phase shift matrices during charging process and offloading process. Then, the non-convex optimization problem is transformed into four sub-problems solved by alternative optimization approach. Numerical results show that the IRS assisted WPT-MEC system with cooperation offloading scheme can significantly improve the performance of MEC system.

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Publication Details

Journal
Alexandria Engineering Journal
Published
2025-09-24
DOI
https://doi.org/10.1016/j.aej.2025.09.020
Primary Topic
Geochemistry and Geologic Mapping
Type
article
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article

IRS-assisted cooperative offloading in integrated wireless power transfer and mobile edge computation system

Alexandria Engineering Journal
Geochemistry and Geologic Mapping
article

IRS-assisted cooperative offloading in integrated wireless power transfer and mobile edge computation system

article en

Abstract

The intelligent reflecting surface (IRS) can intelligently control the wireless communication environment to improve communication quality and wireless power transfer (WPT) technology enables wireless devices powered over the air by dedicated wireless power transmitters for communications. Hence, the integration of IRS and WPT is a promising technology to provide sustainable energy supply and improve computing service in mobile edge computing (MEC) system. Inspired by this, we consider an IRS assisted wireless power transfer-mobile edge computing (WPT-MEC) system, where a hybrid access point (HAP) with server is deployed to charge the low-power wireless devices for sustainable energy supply by the radio-frequency (RF) signal. And the cooperative offloading scheme is adopted in such a system to improve the computation performance of wireless devices, in which the surrounding near devices with idle computation resource are enabled as helpers to use the harvested energy help far device execute computing tasks. All the devices are subject to the energy balance constraints, thus their energy consumption does not exceed the harvested energy from HAP. Under above setup, we maximize the total computation bits for all devices by jointly optimizing the time allocation, power allocation, local computing capability and IRS phase shift matrices during charging process and offloading process. Then, the non-convex optimization problem is transformed into four sub-problems solved by alternative optimization approach. Numerical results show that the IRS assisted WPT-MEC system with cooperation offloading scheme can significantly improve the performance of MEC system.

Alexandria Engineering JournalVol. 130
Jingchu University of Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 28%
Geochemistry and Geologic Mapping
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