Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks
Industrial Internet-of-Things (IIoT) applications in sectors such as energy, manufacturing, healthcare, transportation, and logistics employ intelligent devices, sensors, and connected terminals to improve operational efficiency. However, the IIoT ecosystem faces communication and computation challe...
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IEEE
2025-01-01
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| Online Access: | https://ieeexplore.ieee.org/document/10908631/ |
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| author | Ashu Taneja Shalli Rani Wadii Boulila |
| author_facet | Ashu Taneja Shalli Rani Wadii Boulila |
| author_sort | Ashu Taneja |
| collection | DOAJ |
| description | Industrial Internet-of-Things (IIoT) applications in sectors such as energy, manufacturing, healthcare, transportation, and logistics employ intelligent devices, sensors, and connected terminals to improve operational efficiency. However, the IIoT ecosystem faces communication and computation challenges due to limited connectivity and network resources. Edge computing resources help reduce network congestion. This paper introduces a sixth-generation (6G) communication framework that integrates intelligent reflecting surfaces (IRSs) with non-orthogonal multiple access (NOMA) for mobile edge computing (MEC) systems. The IRS-NOMA approach enables multiple users to offload their tasks simultaneously by adapting the communication environment, thus minimizing offloading delays. Additionally, we propose a resource control algorithm that assigns cell-edge user clusters to specific IRSs based on optimal IRS phase shift and channel correlation criteria. The system outage probability and achievable rate are derived and supported by a comprehensive mathematical analysis. Results indicate that the proposed approach achieves an outage probability of <inline-formula> <tex-math notation="LaTeX">$10^{-5}$ </tex-math></inline-formula> for a transmit power P of 20 dBm with IRS reflecting elements <inline-formula> <tex-math notation="LaTeX">$N = 64$ </tex-math></inline-formula>. Moreover, the achievable rate reaches 5.6 bps/Hz at <inline-formula> <tex-math notation="LaTeX">$P = 20$ </tex-math></inline-formula> dBm. A comparison with two conventional baseline approaches is also provided. |
| format | Article |
| id | doaj-art-dcf445ee8a224015b781f9e589643c77 |
| institution | OA Journals |
| issn | 2644-125X |
| language | English |
| publishDate | 2025-01-01 |
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| series | IEEE Open Journal of the Communications Society |
| spelling | doaj-art-dcf445ee8a224015b781f9e589643c772025-08-20T02:12:24ZengIEEEIEEE Open Journal of the Communications Society2644-125X2025-01-0162757276510.1109/OJCOMS.2025.354701110908631Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT NetworksAshu Taneja0https://orcid.org/0000-0002-6468-3686Shalli Rani1https://orcid.org/0000-0002-8474-9435Wadii Boulila2https://orcid.org/0000-0003-2133-0757Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaChitkara University Institute of Engineering and Technology, Chitkara University, Punjab, IndiaRobotics and Internet-of-Things Laboratory, Prince Sultan University, Riyadh, Saudi ArabiaIndustrial Internet-of-Things (IIoT) applications in sectors such as energy, manufacturing, healthcare, transportation, and logistics employ intelligent devices, sensors, and connected terminals to improve operational efficiency. However, the IIoT ecosystem faces communication and computation challenges due to limited connectivity and network resources. Edge computing resources help reduce network congestion. This paper introduces a sixth-generation (6G) communication framework that integrates intelligent reflecting surfaces (IRSs) with non-orthogonal multiple access (NOMA) for mobile edge computing (MEC) systems. The IRS-NOMA approach enables multiple users to offload their tasks simultaneously by adapting the communication environment, thus minimizing offloading delays. Additionally, we propose a resource control algorithm that assigns cell-edge user clusters to specific IRSs based on optimal IRS phase shift and channel correlation criteria. The system outage probability and achievable rate are derived and supported by a comprehensive mathematical analysis. Results indicate that the proposed approach achieves an outage probability of <inline-formula> <tex-math notation="LaTeX">$10^{-5}$ </tex-math></inline-formula> for a transmit power P of 20 dBm with IRS reflecting elements <inline-formula> <tex-math notation="LaTeX">$N = 64$ </tex-math></inline-formula>. Moreover, the achievable rate reaches 5.6 bps/Hz at <inline-formula> <tex-math notation="LaTeX">$P = 20$ </tex-math></inline-formula> dBm. A comparison with two conventional baseline approaches is also provided.https://ieeexplore.ieee.org/document/10908631/6GIIoTedge computingtask offloadingIRSNOMA |
| spellingShingle | Ashu Taneja Shalli Rani Wadii Boulila Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks IEEE Open Journal of the Communications Society 6G IIoT edge computing task offloading IRS NOMA |
| title | Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks |
| title_full | Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks |
| title_fullStr | Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks |
| title_full_unstemmed | Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks |
| title_short | Resource Control in IRS Assisted Multi-Access Edge Computing for Sustainable 6G IIoT Networks |
| title_sort | resource control in irs assisted multi access edge computing for sustainable 6g iiot networks |
| topic | 6G IIoT edge computing task offloading IRS NOMA |
| url | https://ieeexplore.ieee.org/document/10908631/ |
| work_keys_str_mv | AT ashutaneja resourcecontrolinirsassistedmultiaccessedgecomputingforsustainable6giiotnetworks AT shallirani resourcecontrolinirsassistedmultiaccessedgecomputingforsustainable6giiotnetworks AT wadiiboulila resourcecontrolinirsassistedmultiaccessedgecomputingforsustainable6giiotnetworks |