A Polar Code Based Unsourced Random Access for the Gaussian MAC

Marshakov, Evgeny; Balitskiy, Gleb; Andreev, Kirill; Frolov, Alexey

doi:10.1109/vtcfall.2019.8891583

Cited by 83 publications

(62 citation statements)

References 22 publications

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“…Several lowcomplexity schemes aiming at reaching the finite-blocklength achievability bounds in [1] are devised in the subsequent literature. These include solutions based on T-fold Aloha [2]- [6], splitting the payload [7]- [9], sparsifying codeword bits [10]- [15], and random spreading [16], [17] approaches.…”

Section: Introductionmentioning

confidence: 99%

Random Spreading for Unsourced MAC With Power Diversity

Ahmadi

Duman

2021

IEEE Commun. Lett.

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We propose an improvement of the random spreading approach with polar codes for unsourced multiple access, for which each user first encodes its message by a polar code, and then the coded bits are spread using a random spreading sequence. The proposed approach divides the active users into different groups, and employs different power levels for each group in such a way that the average power constraint is satisfied. We formulate and solve an optimization problem to determine the number of groups, and the corresponding user numbers and power levels. Extensive simulations show that the proposed approach outperforms the existing methods, especially when the number of active users is large.

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Section: Introductionmentioning

confidence: 99%

Random Spreading for Unsourced MAC With Power Diversity

Ahmadi

Duman

2021

IEEE Commun. Lett.

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“…Furthermore, Feng et al [20] proposed an iterative adjustable soft list (IASCL) polar decoder, which relied on the soft cancellation (SCAN) polar decoding principle for generating soft decisions for the entire candidate lists. IDD operating on the basis of LLRs for polar-coded multiple access systems have been studied in [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Soft-Output Successive Cancellation Stack Polar Decoder

Xiang

Liu

Maunder

et al. 2021

IEEE Trans. Veh. Technol.

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“…Over the last few years, there has been great interest in developing efficient lowcomplexity schemes for the unsourced random access channel [2][3][4][5][6][7][8][9][10][11][12][13][14][15]. A natural approach for this setup is for all users to transmit codewords from the same codebook.…”

Section: Introductionmentioning

confidence: 99%

On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel

Romanov

Ordentlich

2021

Entropy

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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 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.

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A Polar Code Based Unsourced Random Access for the Gaussian MAC

Cited by 83 publications

References 22 publications

Random Spreading for Unsourced MAC With Power Diversity

Random Spreading for Unsourced MAC With Power Diversity

Soft-Output Successive Cancellation Stack Polar Decoder

On Compressed Sensing of Binary Signals for the Unsourced Random Access Channel

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