Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system
Abstract In order to improve the performance of the mobile edge computing (MEC) system, the intelligent reflecting surface (IRS) has recently been included. This paper investigates the computation performance of an IRS‐aided MEC system, where an access point services multi‐MEC devices by utilizing t...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Wiley
2023-04-01
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| Series: | IET Communications |
| Subjects: | |
| Online Access: | https://doi.org/10.1049/cmu2.12582 |
| _version_ | 1797847754004758528 |
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| author | Chao Yu Yixuan Li Wenwu Xie Peng Zhu Xin Peng |
| author_facet | Chao Yu Yixuan Li Wenwu Xie Peng Zhu Xin Peng |
| author_sort | Chao Yu |
| collection | DOAJ |
| description | Abstract In order to improve the performance of the mobile edge computing (MEC) system, the intelligent reflecting surface (IRS) has recently been included. This paper investigates the computation performance of an IRS‐aided MEC system, where an access point services multi‐MEC devices by utilizing two distributed IRSs to operate a partial offloading strategy. Through collaboratively constructing the cooperative passive beamforming at the two IRSs, the central processing unit (CPU) frequency, the offloading time allocation, and the transmit power of users, an optimization problem is constructed to maximize the sum computation rate of the proposed system. To tackle this non‐convex issue, the authors first illustrate that the design of passive beamforming is independent to optimize other variables and propose to solve it alternatively. Then the joint optimization problem of other parameters is proved to be a convex problem and is resolvable by adopting the Lagrange dual approach. Compared with the benchmark schemes, the simulation outcomes demonstrated that the performance of the proposed system is vastly improved by deploying two distributed IRSs. |
| first_indexed | 2024-04-09T18:16:27Z |
| format | Article |
| id | doaj.art-3b5f3301802e4cadb1e79004bad236d7 |
| institution | Directory Open Access Journal |
| issn | 1751-8628 1751-8636 |
| language | English |
| last_indexed | 2024-04-09T18:16:27Z |
| publishDate | 2023-04-01 |
| publisher | Wiley |
| record_format | Article |
| series | IET Communications |
| spelling | doaj.art-3b5f3301802e4cadb1e79004bad236d72023-04-13T04:07:16ZengWileyIET Communications1751-86281751-86362023-04-0117779079610.1049/cmu2.12582Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing systemChao Yu0Yixuan Li1Wenwu Xie2Peng Zhu3Xin Peng4School of Information Science and Engineering Hunan Institute of Science and Technology Yueyang ChinaSchool of Information Science and Engineering Hunan Institute of Science and Technology Yueyang ChinaSchool of Information Science and Engineering Hunan Institute of Science and Technology Yueyang ChinaSchool of Information Science and Engineering Hunan Institute of Science and Technology Yueyang ChinaSchool of Information Science and Engineering Hunan Institute of Science and Technology Yueyang ChinaAbstract In order to improve the performance of the mobile edge computing (MEC) system, the intelligent reflecting surface (IRS) has recently been included. This paper investigates the computation performance of an IRS‐aided MEC system, where an access point services multi‐MEC devices by utilizing two distributed IRSs to operate a partial offloading strategy. Through collaboratively constructing the cooperative passive beamforming at the two IRSs, the central processing unit (CPU) frequency, the offloading time allocation, and the transmit power of users, an optimization problem is constructed to maximize the sum computation rate of the proposed system. To tackle this non‐convex issue, the authors first illustrate that the design of passive beamforming is independent to optimize other variables and propose to solve it alternatively. Then the joint optimization problem of other parameters is proved to be a convex problem and is resolvable by adopting the Lagrange dual approach. Compared with the benchmark schemes, the simulation outcomes demonstrated that the performance of the proposed system is vastly improved by deploying two distributed IRSs.https://doi.org/10.1049/cmu2.12582cooperative beamformingintelligent reflecting surfacemobile edge computingpartial computation offloadingresource allocation |
| spellingShingle | Chao Yu Yixuan Li Wenwu Xie Peng Zhu Xin Peng Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system IET Communications cooperative beamforming intelligent reflecting surface mobile edge computing partial computation offloading resource allocation |
| title | Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system |
| title_full | Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system |
| title_fullStr | Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system |
| title_full_unstemmed | Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system |
| title_short | Computation rate optimization for double‐intelligent reflecting surface aided mobile edge computing system |
| title_sort | computation rate optimization for double intelligent reflecting surface aided mobile edge computing system |
| topic | cooperative beamforming intelligent reflecting surface mobile edge computing partial computation offloading resource allocation |
| url | https://doi.org/10.1049/cmu2.12582 |
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