Sparse Kronecker-Product Coding for Unsourced Multiple Access

TL;DR

This paper introduces a novel sparse Kronecker-product coding scheme for unsourced multiple access, combining sparse and error-correcting codes with iterative decoding and interference cancellation to improve performance.

Contribution

The paper proposes a new SKP coding scheme with an iterative decoding algorithm and CRC-aided interference cancellation, outperforming existing methods in unsourced multiple access.

Findings

Outperforms state-of-the-art schemes in simulations

Approaches the random coding bound within 0.1 dB at code length 30000

Maintains low error rates with many active users

Abstract

In this paper, a sparse Kronecker-product (SKP) coding scheme is proposed for unsourced multiple access. Specifically, the data of each active user is encoded as the Kronecker product of two component codewords with one being sparse and the other being forward-error-correction (FEC) coded. At the receiver, an iterative decoding algorithm is developed, consisting of matrix factorization for the decomposition of the Kronecker product and soft-in soft-out decoding for the component sparse code and the FEC code. The cyclic redundancy check (CRC) aided interference cancellation technique is further incorporated for performance improvement. Numerical results show that the proposed scheme outperforms the state-of-the-art counterparts, and approaches the random coding bound within a gap of only 0.1 dB at the code length of 30000 when the number of active users is less than 75, and the error rate can be made very small even if the number of active users is relatively large.