Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25948
Title: Joint Optimization for Cooperative Computing Framework in Double-IRS-Aided MEC Systems
Authors: Zhou, Y
Pan, C
Yeoh, PL
Wang, K
Ma, Z
Vucetic, B
Li, Y
Keywords: double-IRS;cooperative computing;MEC
Issue Date: 7-Feb-2023
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Citation: Zhou, Y. et al. (2023) 'Joint Optimization for Cooperative Computing Framework in Double-IRS-Aided MEC Systems', IEEE Wireless Communications Letters, 12 (5), pp. 779 - 783. doi: 10.1109/lwc.2023.3243031.
Abstract: This letter investigates a cooperative task computing framework, where the source node partially offloads its computational task to multiple user equipments (UEs) aided by double intelligent reflecting surfaces (IRSs). With the aim of maximizing the total amount of computing task subject to latency and power constraints, we highlight an interesting tradeoff between the transmit power and the computing power at the source node and optimize the computing frequency resources as well as phase shift matrices for double IRSs. Numerical results verify the power allocation tradeoff and demonstrate the superiority of our double-IRS-aided solution in terms of maximizing the total amount of computing task over other benchmark strategies.
URI: https://bura.brunel.ac.uk/handle/2438/25948
DOI: https://doi.org/10.1109/lwc.2023.3243031
ISSN: 2162-2337
Other Identifiers: ORCID iD: Yi Zhou https://orcid.org/0000-0001-6407-068X
ORCID iD: Cunhua Pan https://orcid.org/0000-0001-5286-7958
ORCID iD: Phee Lep Yeoh https://orcid.org/0000-0002-2516-4226
ORCID iD: Kezhi Wang https://orcid.org/0000-0001-8602-0800
ORCID iD: Zheng Ma https://orcid.org/0000-0002-0251-1483
ORCID iD: Branka Vucetic https://orcid.org/0000-0002-2700-2001
ORCID iD: Yonghui Li https://orcid.org/0000-0001-7702-1123
Appears in Collections:Dept of Computer Science Research Papers

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