# Sparse IDMA: A Joint Graph-Based Coding Scheme for Unsourced Random Access

## TL;DR

This paper proposes a novel joint graph-based coding scheme called Sparse IDMA for unsourced random access, combining compressive sensing and multi-user coding to improve decoding efficiency and performance.

## Contribution

It introduces a new coding framework that integrates compressive sensing with IDMA principles for unsourced multiple access, enabling low-complexity joint decoding.

## Key findings

- Achieves performance comparable to existing low-complexity schemes.
- Employs a graph-based approach to facilitate joint decoding.
- Supported by numerical simulations demonstrating effectiveness.

## Abstract

This article introduces a novel communication paradigm for the unsourced, uncoordinated Gaussian multiple access problem. The major components of the envisioned framework are as follows. The encoded bits of every message are partitioned into two groups. The first portion is transmitted using a compressive sensing scheme, whereas the second set of bits is conveyed using a multi-user coding scheme. The compressive sensing portion is key in sidestepping some of the challenges posed by the unsourced aspect of the problem. The information afforded by the compressive sensing is employed to create a sparse random multi-access graph conducive to joint decoding. This construction leverages the lessons learned from traditional IDMA into creating low-complexity schemes for the unsourced setting and its inherent randomness. Under joint message-passing decoding, the proposed scheme offers comparable performance to existing low-complexity alternatives. Findings are supported by numerical simulations.