LTE-Advanced is one of the latest generations of mobile communication systems that supports, beside voice and data communication services, the Internet of Things and machine-to-machine communication services. Collisions occur during radio access, due to an increased request of the uplink channel, and have negative impact on the quality of service. The 3GPP has proposed for this purpose, among others solutions, the Access Class Barring to alleviate the problem. In our previous work, we have proposed the Advanced ACB (A-ACB) that significantly reduces the collisions responsible of the congestion in LTE-A network. The A-ACB combines congestion detection method that we have proposed, with the 3GPP native ACB. The simulations results have showed that A-ACB gives much better results compared to basic ACB. Furthermore, it is less complex and easy to implement and does not require large investments from network operators.

In this paper, we propose the detailed analysis of the collisions and connection requests success events that occur in the network in the context of an increased request of the uplink channel, during radio access. The methodology is based on mathematical modeling of the collision detection of UEs.

The simulations are operated considering 1000 terminals candidates to network access. The results obtained show that the collisions and success requests during UEs connection to the network are randomly distributed among UEs. The originality of this work resides in the fact that it shows not only the detailed distribution of the collisions of the UEs but also shows the image of this distribution.

LTE-Advanced is one of the latest generations of mobile communication systems that supports, in addition to voice and data communications services, the Internet Of Things and machine-to-machine communication services. Collisions occur during radio access, due an increasing solicitation of the uplink channel, and have negative impact on the quality of service. The 3GPP has proposed for this purpose; among others solutions, the Access Class Baring to alleviate the problem. In our previous work [4], we have proposed the Advanced (A-ACB) that significantly reduces the collisions responsible of the congestion in LTE-A network. The A-ACB combines congestion detection method that we have proposed in [10] with the 3GPP native ACB. The simulations results have showed that the A-ACB give much better results compared to basic ACB. Furthermore, it is less complex and easy to implement. Also, it does not require large inverstment for network operators. In this paper, we proposed the detailed analysis of collision and connexion event that occurs in the network in the context of an increased solicitation of the uplink channel, during radio access. The methodolgy is based on mathematical modeling of the collision detection of UEs. The simulations are operated considering 1000 terminal candidates to network access. Th results obtained show that the collisions and connexions network are randomly distributed among UEs. The originality of this work resides in the fact that it shows not only the detailed distribution of the collision of the UEs but also shows the image of this distribution.

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Dr. MBAINAIBEYE JEROME