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SCMA-enabled multi-cell edge computing networks : design and optimization
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Liu, Pengtao, An, Kang, Lei, Jing, Liu, Wei, Sun, Yifu, Zheng, Gan and Chatzinotas, Symeon (2023) SCMA-enabled multi-cell edge computing networks : design and optimization. IEEE Transactions on Vehicular Technology, 72 (6). pp. 7987-8003. doi:10.1109/tvt.2023.3242422 ISSN 1939-9359.
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WRAP-SCMA-enabled-multi-cell-edge-Zheng-2023.pdf - Accepted Version - Requires a PDF viewer. Download (14Mb) | Preview |
Official URL: https://doi.org/10.1109/tvt.2023.3242422
Abstract
Multi-access edge computing (MEC) is regarded as a promising approach for providing resource-constrained mobile devices with computing resources through task offloading. Sparse code multiple access (SCMA) is a code-domain non-orthogonal multiple access (NOMA) scheme that can meet the demands of multi-cell MEC networks for high data transmission rates and massive connections. In this paper, we propose an optimization framework for SCMA-enabled multi-cell MEC networks. The joint resource allocation and computation offloading problem is formulated to minimize the system cost, which is defined as the weighted energy cost and latency. Due to the nonconvexity of the proposed optimization problem induced by the coupled optimization variables, we first propose an algorithm based on the block coordinate descent (BCD) method to iteratively optimize the transmit power and edge computing resources allocation by deriving closed-form solutions, and further develop an improved low-complexity simulated annealing (SA) algorithm to solve the computation offloading and multi-cell SCMA codebook allocation problem. To solve the problem of partial state observation and timely decision-making in long-term optimization environment, we put forward a multiagent deep deterministic policy gradient (MADDPG) algorithm with centralized training and distributed execution. Furthermore, we extend the framework to the partial offloading case and propose an algorithm based on alternating convex search for solving the task offloading ratio. Numerical results show that the proposed multi-cell SCMA-MEC scheme achieves lower energy consumption and system latency in comparison to the orthogonal frequency division multiple access (OFDMA) and power-domain (PD) NOMA techniques.
Item Type: | Journal Article | |||||||||
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Alternative Title: | Sparse code multiple access-enabled multi-cell edge computing networks : design and optimization | |||||||||
Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | |||||||||
SWORD Depositor: | Library Publications Router | |||||||||
Library of Congress Subject Headings (LCSH): | Multiple access protocols (Computer network protocols), Internet of things, Edge computing, Information resources management, Digital communication | |||||||||
Journal or Publication Title: | IEEE Transactions on Vehicular Technology | |||||||||
Publisher: | IEEE | |||||||||
ISSN: | 1939-9359 | |||||||||
Official Date: | June 2023 | |||||||||
Dates: |
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Volume: | 72 | |||||||||
Number: | 6 | |||||||||
Page Range: | pp. 7987-8003 | |||||||||
DOI: | 10.1109/tvt.2023.3242422 | |||||||||
Status: | Peer Reviewed | |||||||||
Publication Status: | Published | |||||||||
Reuse Statement (publisher, data, author rights): | © 2023 Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | |||||||||
Access rights to Published version: | Restricted or Subscription Access | |||||||||
Date of first compliant deposit: | 5 September 2023 | |||||||||
Date of first compliant Open Access: | 5 September 2023 | |||||||||
RIOXX Funder/Project Grant: |
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