Blind Multi-user Detection for Autonomous Grant-free High-Overloading MA without Reference Signal

TL;DR

This paper introduces a novel blind multi-user detection framework for autonomous grant-free high-overloading non-orthogonal multiple access, enhancing 5G massive Machine Type Communications without relying on reference signals.

Contribution

It presents a comprehensive blind detection framework combining code word-level SIC, blind activation detection, blind equalization, and blind channel estimation for autonomous grant-free NOMA.

Findings

Effective blind detection without reference signals

Improved detection accuracy in high-overloading scenarios

Enhanced suitability for 5G massive MTC

Abstract

In this paper, a novel blind multi-user detection(MUD) framework for autonomous grant-free high-overloading non-orthogonal multiple access is introduced in detail aimed at fulfilling the requirements of fifth-generation massive Machine Type Communications. From the perspective of the transmitter side, pros and cons regarding diverse types of emerging grant-free transmission, particularly autonomous grant-free, are elaborated and presented in a comparative manner. In the receiver end,code word-level successive interference cancellation (CL-SIC) is revealed as the main framework to perform MUD. In addition, underpinning state-of-art blind ideas such as blind activation detection taking advantage of the statistical metric of the aggregate signals, blind equalization based on the constellation's simple geometric character of low order modulation symbols, and blind channel estimation employing solely the successfully decoded code words are explained.