Abstract
The Long Term Evolution - LTE - is one of the very last evolutions in mobile communication systems that offer a much wider bandwidth than its predecessors. That is why it is very much in demand for a massive deployment of the Internet of Things (IoT) also called Machine to Machine communication or Machine Type Communication (MTC). With the IoT, the network is subject to recurrent congestion when densely charged which is due to increased uplink solicitation. MTC devices must complete the RACH process to access the network. Collisions occur during this process that leads to the congestion which, in turn, has a negative impact on the quality of service. The Third Generation Partnership Project (3GPP) provided some solutions to alleviate the problem. In this paper we propose a congestion detection method since 3GPP only proposed contention resolution methods. We first determine the interval of use of preambles during which the success rate is the highest. By doing so, we determine the maximal preamble utilization threshold (Rlimit) beyond which quality of service is no more guaranteed. The novelty with this method is that once Rlimit threshold is reached, a contention resolution scheme could be activated and will remain so until the threshold drops below Rlimit. Our method can give better results if applied to contention resolution methods. Moreover it is simple, less complex and easy to implement in the LTE. Moreover, it does not require large investments.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsReferences
Atzori, L., Iera, A., Morabito, G.: The Internet of Things: a survey. J. Comput. Netw. 54(15), 2787–2805 (2010)
Xia, N., Yang, C.-S.: Recent advances in machine-to-machine communications. J. Comput. Commun. 4, 107–111 (2016)
IEEE: Machine to Machine (M2M) communications technical report. IEEE 802.16p-10/0005, November 2010
Gartner: Gartner says the internet of things installed base will grow to 26 billion units by 2020 (2013)
Han, X., Lim, T.J., Xu, J.: Heterogeneous access class barring with QoS guarantee in machine-type communications. Trans. Emerg. Telecommun. Technol. 28, e2959 (2015)
http://www.rfwireless-world.com/Terminology/LTE-PRACH-Physical-Random-Access-Channel.html. Accessed 12 Apr 2017
Sesia, S., Toufik, I., Baker, M.: LTE–The UMTS Long Term Evolution: From Theory to Practice. Wiley, Hoboken (2009)
GPP TR 37.868 V11.0.0: Study on RAN Improvements for Machine-type Communications, September 2011
GPP:R2-100182: Access control of MTC devices. 3GPP TSG RAN WG2 Meeting 68bis, Valencia, Spain (2010)
GPP:R2-103143: Discussion on separating RACH resources for MTC. Alcatel-lucent Shanghai Bell, Alcatel-lucent (2010)
Larmo, A., Susitaival, R.: RAN overload control for machine type communications in LTE. In: 2012 IEEE GLOBECOM Workshops (GC Workshops), pp. 1626–163 (2012)
Cheng, R., Chen, J., Chen, D., Wei, C.: Modeling and analysis of an extended access barring scheme for machine-type communications in LTE-A networks. IEEE Trans. Wirel. Commun. 14(6), 2956–2968 (2015)
Lien, S.-Y., Liau, T.-H., Kao, C.-Y., Chen, K.-C.: Cooperative access class barring for machine-to-machine communications. IEEE Trans. Wirel. Commun. 11(1), 27–32 (2012)
Jiang, T., Tan, X., Luan, X., Zhang, X., Wu, J.: Evolutionary game based access class barring for machine-to-machine communications. In: 2014 16th International Conference on Advanced Communication Technology (ICACT), pp. 832–835, February 2014
Cheng, J.-P., Lee, C., Lin, T.-M.: Prioritized random access with dynamic access barring for RAN overload in 3GPP LTE-a networks. In: 2011 IEEE GLOBECOM Workshops (GC Workshops), pp. 368–372 (2011)
Lin, G.-Y., Chang, S.-R., Wei, H.-Y.: Estimation and adaptation for bursty LTE random access. IEEE Trans. Veh. Technol. 65, 2560–2577 (2015)
Lee, K.-D., Kim, S., Yi, B.: Throughput comparison of random access methods for M2M service over LTE networks. In: 2011 GLOBECOM Workshops (GC Workshops), December, pp. 373–377
GPP:R2-113328: Dynamic separate RACH resources for MTC. 3GPP TSG RAN WG2 74. Institute for Information Industry (III), Coiler Corporation (2011)
Pang, Y.-C., Chao, S.-L., Lin, G.-Y., Wei, H.-Y.: Network access for m2m/h2h hybrid systems: a game theoretic approach. Commun. Lett. 18(5), 845–848 (2014)
Jian, X., Jia, Y., Zeng, X., Yang, J.: A novel class-dependent back-off scheme for machine type communication in LTE systems. In: 2013 22nd Wireless and Optical Communication Conference (WOCC), pp. 135–140 (2013)
Lien, S.-Y., Chen, K.-C., Lin, Y.: Toward ubiquitous massive accesses in 3GPP machine-to-machine communications. IEEE Commun. Mag. 49(4), 66–74 (2011)
GPP:R2-112247: Merits of the slotted access methods for MTC. Alcatel-lucent Shanghai Bell, Alcatel-lucent (2011)
G. R. 104873: Comparing push and pull based approaches for MTC. 3rd Generation Partnership Project (2010)
GPP:R2-104007: Pull vs push approach for MTC. 3GPP TSG RAN WG2 70bis, Stockholm, Sweden (2010)
GPP:R2-102781: Paging and downlink transmission for MTC. 3GPP TSG RAN WG2 Meeting 70, Montreal, Canada (2010)
Wei, C.-H., Cheng, R.-G., Tsao, S.-L.: Performance analysis of group paging for machine-type communications in LTE networks. IEEE Trans. Veh. Technol. 62(7), 3371–3382 (2013)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Bouba, G.M., Mbainaibeye, J., Kouawa Tamgno, J., Lishou, C. (2019). LTE-Advanced Random Access Channel Congestion Detection Method for IoT. In: Mendy, G., Ouya, S., Dioum, I., Thiaré, O. (eds) e-Infrastructure and e-Services for Developing Countries. AFRICOMM 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 275. Springer, Cham. https://doi.org/10.1007/978-3-030-16042-5_5
Download citation
DOI: https://doi.org/10.1007/978-3-030-16042-5_5
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-16041-8
Online ISBN: 978-3-030-16042-5
eBook Packages: Computer ScienceComputer Science (R0)