DocumentCode :
132003
Title :
Machine-to-Machine traffic characterization: Models and case study on integration in LTE
Author :
Smiljkovic, Katerina ; Atanasovski, Vladimir ; Gavrilovska, Liljana
Author_Institution :
Fac. of Electr. Eng. & Inf. Technol., Ss. Cyril & Methodius Univ. in Skopje, Skopje, Macedonia
fYear :
2014
fDate :
11-14 May 2014
Firstpage :
1
Lastpage :
5
Abstract :
This paper analyses and compares three different models for Machine-to-Machine (M2M) traffic and investigates the possibility of integrating generated M2M traffic into a Long Term Evolution (LTE) network. According to the authors´ knowledge, current M2M traffic models assume that 1) the M2M traffic is aggregated traffic with constant arrival rate and 2) the cellular networks have enough resources to support the generated traffic. However, neither 1) nor 2) are true for M2M traffic in cellular networks. This paper analyses M2M traffic with variable arrival rate under the assumption that the LTE network has limited resources. The results showcase the characteristics of the M2M traffic in a more realistic manner pinpointing the differences from the standard traffic in cellular network. They reveal that the traffic is not self-similar, but only for large number of machines. Also, the results give insight into the design parameters that should be considered for LTE in order to support M2M traffic.
Keywords :
Long Term Evolution; cellular radio; telecommunication traffic; LTE network; Long Term Evolution network; M2M traffic models; cellular networks; machine-to-nachine traffic characterization; variable arrival rate; Analytical models; Complexity theory; Correlation; Data models; Long Term Evolution; Probability density function; Uplink; LTE network; Machine-to-Machine communications; traffic modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Wireless Communications, Vehicular Technology, Information Theory and Aerospace & Electronic Systems (VITAE), 2014 4th International Conference on
Conference_Location :
Aalborg
Print_ISBN :
978-1-4799-4626-6
Type :
conf
DOI :
10.1109/VITAE.2014.6934482
Filename :
6934482
Link To Document :
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