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On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel
[article]
2021
arXiv
pre-print
Motivated by applications in unsourced random access, this paper develops a novel scheme for the problem of compressed sensing of binary signals. In this problem, the goal is to design a sensing matrix A and a recovery algorithm, such that the sparse binary vector 𝐱 can be recovered reliably from the measurements 𝐲=A𝐱+σ𝐳, where 𝐳 is additive white Gaussian noise. We propose to design A as a parity check matrix of a low-density parity-check code (LDPC), and to recover 𝐱 from the measurements 𝐲
arXiv:2105.05350v1
fatcat:ndlyuic36jbjpnzhf7qudgnjwe