- Title
- DQN-based resource allocation for NOMA-MEC-aided multi-source data stream
- Creator
- Ling, Jing; Xia, Junjuan; Zhu, Fusheng; Gao, Chongzhi; Lai, Shiwei; Balasubramanian, Venki
- Date
- 2023
- Type
- Text; Journal article
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/194037
- Identifier
- vital:18304
- Identifier
-
https://doi.org/10.1186/s13634-023-01005-2
- Identifier
- ISSN:1687-6172 (ISSN)
- Abstract
- This paper investigates a non-orthogonal multiple access (NOMA)-aided mobile edge computing (MEC) network with multiple sources and one computing access point (CAP), in which NOMA technology is applied to transmit multi-source data streams to CAP for computing. To measure the performance of the considered NOMA-aided MEC network, we first design the system cost as a linear weighting function of energy consumption and delay under the NOMA-aided MEC network. Moreover, we propose a deep Q network (DQN)-based offloading strategy to minimize the system cost by jointly optimizing the offloading ratio and transmission power allocation. Finally, we design experiments to demonstrate the effectiveness of the proposed strategy. Specifically, the designed strategy can decrease the system cost by about 15% compared with local computing when the number of sources is 5. © 2023, The Author(s).
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Relation
- Eurasip Journal on Advances in Signal Processing Vol. 2023, no. 1 (2023), p.
- Rights
- All metadata describing materials held in, or linked to, the repository is freely available under a CC0 licence
- Rights
- https://creativecommons.org/licenses/by/4.0/
- Rights
- Copyright © 2023, The Author(s)
- Rights
- Open Access
- Subject
- 4006 Communications engineering; 4603 Computer vision and multimedia computation; DQN; MEC; Multi-source data stream; NOMA
- Full Text
- Reviewed
- Funder
- This work was supported by the Key-Area Research and Development Program of Guangdong Province, China (No. 2019B090904014), Science and Technology Projects in Guangzhou (No. 202102010412), and Yangcheng Scholars Research Project of Guangzhou (No. 202032832), and by Science and Technology Program of Guangzhou (No. 202201010047).
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