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Compressive sensing based grant-free access for large-scale distributed networks
  • +3
  • Xiaoyi Yu,
  • YUN LIU,
  • Zikai Wang,
  • Haipeng Zhang,
  • Waiho MOW,
  • Pei Xiao
Xiaoyi Yu
The Beijing R&D Center, Academy for Network and Communications of China Electronics Technology Group Corporation

Corresponding Author:violetxiaoyi@163.com

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YUN LIU
the Academy for Network & Communications of China Electronics Technology Group Corporation
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Zikai Wang
Academy for Network & Communications of China Electronics Technology Group Corporation
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Haipeng Zhang
the Beijing R&D Center, Academy for Network and Communications of China Electronics Technology Group Corporation Shijiazhuang, China
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Waiho MOW
The Hong Kong University of Science and Technology
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Pei Xiao
The State Key Laboratory of ISN, Xidian University
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Abstract

Aiming at the problem of access delay caused by the contention of resource requests from a large-scale distributed Unmanned aerial vehicle (UAV) network leading to unavoidable conflicts, we propose a grant-free access scheme based on the prediction channel. Specifically, we spread the transmit signals over multiple subcarriers by spreading the frequency, and summaries the signal detection problem for grant -free access as a multi-measurement vector (MMV) compression sensing problem. The channel is estimated based on beacon, and the orthogonal approximation message passing (OAMP)-MMV algorithm is used. Sparsity ratio and noise variance are learnt using variational inference (VI). Finally, the likelihood ratio (LLR) is used to identify the active nodes. Simulation results verify that the proposed scheme outperforms various baseline schemes and achieves low-latency and highly reliable random access.
20 Dec 2024Submitted to Electronics Letters
28 Dec 2024Submission Checks Completed
28 Dec 2024Assigned to Editor
28 Dec 2024Review(s) Completed, Editorial Evaluation Pending
30 Dec 2024Reviewer(s) Assigned