RACH overload congestion mechanism for M2M communication in LTE-A: Issues and approaches

Author(s):  
A. H. El Fawal ◽  
A. Mansour ◽  
F. Le Roy ◽  
D. Le Jeune ◽  
A. Hamie
Keyword(s):  
2016 ◽  
Vol E99.B (12) ◽  
pp. 2498-2508
Author(s):  
Daisuke MATSUBARA ◽  
Hitoshi YABUSAKI ◽  
Satoru OKAMOTO ◽  
Naoaki YAMANAKA ◽  
Tatsuro TAKAHASHI

2016 ◽  
Vol 68 ◽  
pp. 42-55 ◽  
Author(s):  
Anum Ali ◽  
Ghalib A. Shah ◽  
Junaid Arshad

Author(s):  
Sourajit Roy ◽  
Pankaj Pathak ◽  
S. Nithya

During the advent of the 21st century, technical breakthroughs and developments took place. Natural Language Processing or NLP is one of their promising disciplines that has been increasingly dynamic via groundbreaking findings on most computer networks. Because of the digital revolution the amounts of data generated by M2M communication across devices and platforms such as Amazon Alexa, Apple Siri, Microsoft Cortana, etc. were significantly increased. This causes a great deal of unstructured data to be processed that does not fit in with standard computational models. In addition, the increasing problems of language complexity, data variability and voice ambiguity make implementing models increasingly harder. The current study provides an overview of the potential and breadth of the NLP market and its acceptance in industry-wide, in particular after Covid-19. It also gives a macroscopic picture of progress in natural language processing research, development and implementation.


2015 ◽  
Vol 2015 ◽  
pp. 1-10
Author(s):  
Fangmin Xu ◽  
Chao Qiu ◽  
Pengbiao Wang ◽  
Xiaokai Liu

With the recently progress of Machine-to-Machine (M2M) communication technology, especially the enormous M2M devices and unique service of M2M, some challenges are emerging to the traditional wireless access and core networks, especially the congestion problem due to simultaneously bursty M2M service. Following this paradigm, the purpose of this paper is to support and optimize the signaling aggregation and barring of M2M services based on cellular network. With LTE network being the example access network, a congestion-aware signaling aggregation and barring scheme is designed considering the various requirements of M2M services and the congestion situation in the network entity. Theoretical analysis and experimental simulations show that this scheme can improve the system efficiency and greatly alleviate the signaling congestion, especially for the bursty M2M service.


Sign in / Sign up

Export Citation Format

Share Document