Optimal Resource Dedication in Grouped Random Access for Massive Machine-Type Communications

TL;DR

This paper proposes an optimized resource dedication strategy for grouped random access in massive Machine-Type Communications, aiming to reduce collisions and power consumption while allowing flexible class preferences.

Contribution

It introduces a novel resource dedication approach that combines resource separation with class preference, improving upon existing random access methods in mMTC.

Findings

Reduces collision rates in mMTC scenarios

Lowers power consumption for device communications

Provides flexible class-specific resource allocation

Abstract

The high risk of random access collisions leads to huge challenge for the deployment massive Machine-Type Communications (mMTC), which cannot be sufficiently overcome by current solutions in LTE/LTE-A networks such as the extended access barring (EAB) scheme. The recently studied approaches of grouped random access have shown a great potential in simultaneously reducing the collision rate and the power consumption in mMTC applications, and exhibit a good compatibility with the concept of random access resource separation. In this work, we propose an optimized resource dedication strategy for grouped random access approaches, which inherits the advantage of resource separation to isolate device classes from each other, while providing an optional class preference with high flexibility and accuracy, which has been usually implemented with access class barring.