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Reconfigurable Intelligent Surface Assisted MEC Offloading in NOMA-Enabled IoT Networks

Chen, Z; Tang, J; Wen, M; Li, Z; Yang, J; Zhang, XY; Wong, KK; (2023) Reconfigurable Intelligent Surface Assisted MEC Offloading in NOMA-Enabled IoT Networks. IEEE Transactions on Communications 10.1109/TCOMM.2023.3277005. (In press). Green open access

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Abstract

Integrating mobile edge computing (MEC) into the Internet of Things (IoT) enables resource-limited mobile terminals to offload part or all of the computation-intensive applications to nearby edge servers. On the other hand, by introducing reconfigurable intelligent surface (RIS), it can enhance the offloading capability of MEC, such that enabling low latency and high throughput. To enhance the task offloading, we investigate the MEC non-orthogonal multiple access (MEC-NOMA) network framework for mobile edge computation offloading with the assistance of a RIS. Different from conventional communication systems, we aim at allowing multiple IoT devices to share the same channel in tasks offloading process. Specifically, the joint consideration of channel assignments, beamwidth allocation, offloading rate and power control is formulated as a multi-objective optimization problem (MOP), which includes minimizing the offloading delay of computing-oriented IoT devices (CP-IDs) and maximizing the transmission rate of communication-oriented IoT devices (CM-IDs). Since the resulting problem is non-convex, we employ ϵ-constraint approach to transform the MOP into the single-objective optimization problems (SOP), and then the RIS-assisted channel assignment algorithm is developed to tackle the fractional objective function. Simulation results corroborate the benefits of our strategy, which can outperforms the other benchmark schemes.

Type: Article
Title: Reconfigurable Intelligent Surface Assisted MEC Offloading in NOMA-Enabled IoT Networks
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/TCOMM.2023.3277005
Publisher version: https://doi.org/10.1109/TCOMM.2023.3277005
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
URI: https://discovery.ucl.ac.uk/id/eprint/10173268
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