Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
167 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
42 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

Grouping-Based Random Access Collision Control for Massive Machine-Type Communication (1704.07857v2)

Published 25 Apr 2017 in cs.NI

Abstract: Massive Machine-Type Communication (mMTC) is expected to be strongly supported by future 5G wireless networks. Its deployment, however, is seriously challenged by the high risk of random access (RA) collision. A popular concept is to reduce RA collisions by clustering mMTC devices into groups, and to connect group members with device-to-device (D2D) links. However, analytical models of this method and discussions about the reliability of D2D links are still absent. In this paper, existing grouping-based solutions are reviewed, an analytical model of grouped RA collision is proposed. Based on the analytical model, the impact of D2D reliability on the collision rate is also investigated. Afterwards, an efficient grouped RA procedure is designed to extend the state-of-the-art with an efficient local group update mechanism against D2D link exceptions.

Citations (23)

Summary

We haven't generated a summary for this paper yet.