Polar Coding and Random Spreading for Unsourced Multiple Access

TL;DR

This paper introduces a new transmission scheme combining polar coding, random spreading, and interference cancellation for unsourced multiple access, achieving improved performance in multi-user detection and decoding.

Contribution

The paper proposes a novel scheme that integrates polar codes with random spreading and successive interference cancellation for unsourced multiple access, enhancing detection and decoding efficiency.

Findings

Outperforms existing low-complexity schemes for up to 225 active users.

Effectively detects active sequences using correlation-based energy detection.

Iterative decoding improves accuracy by subtracting decoded signals.

Abstract

This article presents a novel transmission scheme for the unsourced, uncoordinated Gaussian multiple access problem. The proposed scheme leverages notions from single-user coding, random spreading, minimum-mean squared error (MMSE) estimation, and successive interference cancellation. Specifically, every message is split into two parts: the first fragment serves as the argument to an injective function that determines which spreading sequence should be employed, whereas the second component of the message is encoded using a polar code. The latter coded bits are then spread using the sequence determined during the first step. The ensuing signal is transmitted through a Gaussian multiple-access channel (GMAC). On the receiver side, active sequences are detected using a correlation-based energy detector, thereby simultaneously recovering individual signature sequences and their generating information bits in the form of preimages of the sequence selection function. Using the set of detected active spreading sequences, an MMSE estimator is employed to produce log-likelihood ratios (LLRs) for the second part of the messages corresponding to these detected users. The LLRs associated with each detected user are then passed to a list decoder of the polar code, which performs single-user decoding to decode the second portion of the message. This decoding operation proceeds iteratively by subtracting the interference due to the successfully decoded messages from the received signal, and repeating the above steps on the residual signal. At this stage, the proposed algorithm outperforms alternate existing low-complexity schemes when the number of active uses is below 225.