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Unsourced Random Access With Threshold-Based Feedback
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AI
DOI：10.1109/TCOMM.2023.3312257.png)
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摘要
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In this paper we study feedback mechanisms for unsourced random access (URA) communications. We propose an algorithm to construct feedback packets broadcasted to the users by the base station (BS) and a feedback packet format that allows the users to estimate their channels and infer positive or negative feedback based on the presented thresholding algorithms. We show that the proposed feedback technique leads to a substantial reduction in the packet error rates and signal-to-noise ratios (SNRs) required to support various numbers of active users. We also demonstrate that the proposed feedback imposes a much smaller complexity burden on the users compared to the feedback that acknowledges only successful or only all undecoded users. Finally, we present a theoretical analysis framework that closely matches the experimental results.
Keyword:
Unsourced random access (URA)
feedback
multiple user detection
compressed sensing
期刊
IF:
8.3
论文数:
1.2W
被引数:
3.6W
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