期刊
2019 IEEE INTERNATIONAL SYMPOSIUM ON INFORMATION THEORY (ISIT)
卷 -, 期 -, 页码 2843-2847出版社
IEEE
DOI: 10.1109/isit.2019.8849802
关键词
-
资金
- Alexander-von-Humboldt foundation
- DAAD [57417688]
- DFG [JU 2795/3]
This paper studies the optimal achievable performance of compressed sensing based unsourced random-access communication over the real AWGN channel. Unsourced means that every user employs the same codebook. This paradigm, recently introduced by Polyanskiy, is a natural consequence of a very large number of potential users of which only a finite number is active in each time slot. The resemblance of compressed sensing based communication and sparse regression codes (SPARCs), a novel type of point-to-point channel codes, allows us to design and analyse an efficient unsourced random-access code. Finite blocklength simulations show that the combination of AMP decoding, with suitable approximations, together with an outer code recently proposed by Amalladinne et. al. outperforms state of the art methods in terms of required energy-per-bit at lower decoding complexity.
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