Joint Offloading Policy and Resource Allocation in IRS-aided MEC for IoT Users with Short Packet Transmission
Jalali J, Khalili A, Berkvens R, Famaey J (2023)
Publication Language: English
Publication Type: Conference contribution
Publication year: 2023
Publisher: Institute of Electrical and Electronics Engineers Inc.
Conference Proceedings Title: 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall)
Event location: Hong Kong
ISBN: 979-8-3503-2929-2
DOI: 10.1109/VTC2023-Fall60731.2023.10333867
Abstract
This paper focuses on leveraging a mobile edge computing (MEC) server at an access point (AP) to address the delay and reliability sensitivity requirement of multi-user machine-type communication (MTC). By offloading tasks to the MEC server, latency for low-power MTC devices can be minimized. Meanwhile, intelligent reflecting surfaces (IRSs) are supported to facilitate robust offloading, enhance spectrum efficiency, and improve coverage by influencing incident radio-frequency wave propagation via modifying the phase shifts with passive reflecting components. Therefore, we investigate joint radio resource allocation and edge offloading decision optimization in a multi-user IRS-assisted MEC network, wherein a multi-antenna AP receives information symbols from a set of Internet of Things (IoT) users with short packet transmission. In particular, we minimize the system's power utilization subject to offloading MTC-enabled IoT users' quality of service (QoS) requirements, transmit power feasibility, capacity limitation, and IRS phase shift. The non-convex nature of the formulated problem poses a challenge to solving it effectively. To address this, we propose an efficient iterative algorithm based on successive convex approximation (SCA) and a penalty-based approach for handling unit-modulus constraints in the presence of passive reflecting elements at the IRS. Simulation results demonstrate the superior performance of our algorithm compared to other baseline schemes.
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APA:
Jalali, J., Khalili, A., Berkvens, R., & Famaey, J. (2023). Joint Offloading Policy and Resource Allocation in IRS-aided MEC for IoT Users with Short Packet Transmission. In 2023 IEEE 98th Vehicular Technology Conference (VTC2023-Fall). Hong Kong, CN: Institute of Electrical and Electronics Engineers Inc..
MLA:
Jalali, Jalal, et al. "Joint Offloading Policy and Resource Allocation in IRS-aided MEC for IoT Users with Short Packet Transmission." Proceedings of the 98th IEEE Vehicular Technology Conference, VTC 2023-Fall, Hong Kong Institute of Electrical and Electronics Engineers Inc., 2023.
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