Title
Priority-Based Massive Random Access of M2M Communications in LTE Networks: Throughput Analysis and optimization
Abstract
The machine-to-machine (M2M) communication is a technology that contains massive number of machine type devices (MTDs) and different kinds of applications, with which it is imperative to improve the access efficiency and provide priority-based service. To address this issue, a priority-based analytical framework is proposed in this paper to optimize the network throughput under diverse throughput requirements for M2M communications. Specifically, MTDs are divided into multiple groups according to their applications. The access behavior of each MTD is characterized by a double-queue model. Based on this model, the network throughput is derived as an explicit function of the number of groups and the parameters of each group including the number of MTDs, the aggregate packet arrival rate, the access class barring (ACB) factor and the uniform backoff (UB) window size. To satisfy the diverse service requirements of different applications, a constraint is imposed to ensure a target throughput ratio among groups. The maximum network throughput is then derived under the throughput ratio constraint. Simulation results verify that with the optimal tuning of backoff parameters, the network can achieve the optimal throughput and meet the diverse throughput requirements between groups at the same time irrespective of the number of MTDs in the network.
Year
DOI
Venue
2019
10.1109/ICCChina.2019.8855934
2019 IEEE/CIC International Conference on Communications in China (ICCC)
Keywords
Field
DocType
priority-based massive random access,LTE networks,machine-to-machine communication,machine type devices,priority-based service,priority-based analytical framework,double-queue model,uniform backoff window size,M2M communications,MTD,packet arrival rate,access class barring factor,ACB factor
Optimal tuning,Computer science,Network packet,Computer network,Implicit function,Throughput,Random access
Conference
ISSN
ISBN
Citations 
2377-8644
978-1-7281-0733-2
0
PageRank 
References 
Authors
0.34
10
4
Name
Order
Citations
PageRank
Changwei Zhang141.40
Xinghua Sun243.15
Jun Zhang39511.09
Hongbo Zhu436785.53