Performance and Modeling of Session Setup Procedure Using Random Access Channel
- Authors: Zaripova ER1, Ardila Pinto A1
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Affiliations:
- RUDN University (Peoples’ Friendship University of Russia)
- Issue: Vol 25, No 1 (2017)
- Pages: 9-18
- Section: Mathematical Teletraffic Theory and Telecommunication Networks
- URL: https://journals.rudn.ru/miph/article/view/15160
- DOI: https://doi.org/10.22363/2312-9735-2017-25-1-9-18
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Abstract
We observe nowadays increasing the number of devices using Internet for data transmission in LTE network. Researchers offer their algorithms and methods for base station load reduction. Our approach allows minimizing network resources using Random Access Channel for session setup procedure. We obtain all performance measures for this procedure between user equipment and LTE base station. Procedure includes four messages: preamble transmission on the physical random access channel (Msg1), random access response of existing RACH procedure (Msg2), connection request, a.k.a. Hybrid automatic repeat request on the physical uplink shared channel (Msg3) and connection resolution (Msg4). This approach is used for small data transmission. If two or more devices select the same preamble, then collision occurs, and it is necessary to retransmit another preamble. Similarly, Msg3 may be blocked due to lack of resources. Our analytical model includes the dependence on collision probability. This solution has been proposed by 3GPP technical report 37.868. We obtain such performance measures as collision probability, dependent upon the number of attempts and the overall number of attempts in the period; access success probability; statistics of number of preamble transmissions; statistics of access delay. Numerical experiment demonstrate the accuracy of the proposed analytical model in the form of Markov chains.
About the authors
E R Zaripova
RUDN University (Peoples’ Friendship University of Russia)
Email: ezarip@sci.pfu.edu.ru
Department of Applied Probability and Informatics 6, Miklukho-Maklaya str., Moscow, Russia, 117198
A Ardila Pinto
RUDN University (Peoples’ Friendship University of Russia)
Email: aldemar.ardila@gmail.com
Department of Applied Probability and Informatics 6, Miklukho-Maklaya str., Moscow, Russia, 117198