Grant-free Rateless Multiple Access: A Novel Massive Access Scheme for Internet of Things

TL;DR

This paper introduces a grant-free rateless multiple access scheme for IoT that eliminates registration, reducing latency and signaling, and employs a joint detection and decoding algorithm with performance evaluation via density evolution.

Contribution

It proposes a novel grant-free RMA scheme leveraging access patterns, along with a low-complexity joint detection and decoding algorithm and a density evolution-based performance analysis.

Findings

Reduces signaling overhead and latency in IoT access.

Achieves efficient active user detection and decoding.

Provides a density evolution method for performance evaluation.

Abstract

Rateless Multiple Access (RMA) is a novel non-orthogonal multiple access framework that is promising for massive access in Internet of Things (IoT) due to its high efficiency and low complexity. In the framework, after certain \emph{registration}, each active user respectively transmits to the access point (AP) randomly based on an assigned random access control function (RACf) until receiving an acknowledgement (ACK). In this work, by exploiting the intrinsic access pattern of each user, we propose a grant-free RMA scheme, which no longer needs the registration process as in the original RMA, thus greatly reduces the signalling overhead and system latency. Furthermore, we propose a low-complexity joint iterative detection and decoding algorithm in which the channel estimation, active user detection, and information decoding are done simultaneously. Finally, we propose a method based on density evolution (DE) to evaluate the system performance.