On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel |
| |
Authors: | Elad Romanov Or Ordentlich |
| |
Affiliation: | The Rachel and Selim Benin School of Computer Science and Engineering, Hebrew University of Jerusalem, Jerusalem 919050, Israel; |
| |
Abstract: | 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 can be recovered reliably from the measurements , where 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 from the measurements using a Markov chain Monte Carlo algorithm, which runs relatively fast due to the sparse structure of A. The performance of our scheme is comparable to state-of-the-art schemes, which use dense sensing matrices, while enjoying the advantages of using a sparse sensing matrix. |
| |
Keywords: | unsourced random access compressed sensing low-density parity-check codes glauber dynamics |
|
|