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| Main Author: | |
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| Format: | Preprint |
| Published: |
2022
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2208.10704 |
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| _version_ | 1866913499525939200 |
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| author | Li, Haodong |
| author_facet | Li, Haodong |
| contents | This paper studies the offloading service improvement of multi-access edge computing (MEC) based on backscatter communication (BackCom) assisted non-orthogonal multiple access (BAC-NOMA). A hybrid BAC-NOMA protocol is proposed, where the uplink users backscatter their tasks by leveraging the downlink signal, and then the remaining data is transmitted through uplink NOMA. In particular, a resource allocation problem is formulated to minimize the offloading delay of uplink users. The non-convex problem is transformed into a convex problem, and an iterative algorithm is developed accordingly. Simulation results show that the proposed protocol outperforms the benchmark in terms of offloading delay. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2208_10704 |
| institution | arXiv |
| publishDate | 2022 |
| record_format | arxiv |
| spellingShingle | Delay Minimization for Hybrid BAC-NOMA Offloading in MEC Networks Li, Haodong Information Theory This paper studies the offloading service improvement of multi-access edge computing (MEC) based on backscatter communication (BackCom) assisted non-orthogonal multiple access (BAC-NOMA). A hybrid BAC-NOMA protocol is proposed, where the uplink users backscatter their tasks by leveraging the downlink signal, and then the remaining data is transmitted through uplink NOMA. In particular, a resource allocation problem is formulated to minimize the offloading delay of uplink users. The non-convex problem is transformed into a convex problem, and an iterative algorithm is developed accordingly. Simulation results show that the proposed protocol outperforms the benchmark in terms of offloading delay. |
| title | Delay Minimization for Hybrid BAC-NOMA Offloading in MEC Networks |
| topic | Information Theory |
| url | https://arxiv.org/abs/2208.10704 |