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Erschienen in: The Journal of Supercomputing 8/2021

03.02.2021

Optimal TAL-based registration with cell-based central policy in mobile cellular networks: a semi-Markov process approach

verfasst von: Hee-Seon Jang, Jang Hyun Baek

Erschienen in: The Journal of Supercomputing | Ausgabe 8/2021

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Abstract

LTE networks consist of tracking areas (TAs) or a group of cells, while several TAs constitute a TA list (TAL). The LTE network adopts TAL-based registration, where, if the user equipment (UE) enters a TA that is not in its current TAL, the UE registers the TA to inform the network of its new location. A central policy for TAL allocation, known as a TA-based central policy, was proposed for TAL-based registration. Under the central policy, the TA in which the UE registers its location becomes the central TA of the new TAL. This policy can lessen the possibility of the UE quickly exiting the new TAL. However, considering the actual network architecture, it makes TAL-based registration a challenge to implement. Thus to mitigate this problem, a cell-based central policy is proposed. This study investigates TAL-based registration with cell-based central policy (TbRcc) for LTE networks. TAL-based registration with cell-based central policy and single-cell TA (TbRcc1c) is also proposed to reduce the registration cost and make up the optimal TAL. Furthermore, an improved analysis model is presented to reflect the effect of the implicit registration of calls and obtain the exact cost. Comparing the performance of the proposed scheme with those of classical TAL-based registration and distance-based registration, the performance of the proposed scheme is shown to improve. The results of this study can help research that addresses the mobility management of next-generation networks, as well as LTE networks.

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Metadaten
Titel
Optimal TAL-based registration with cell-based central policy in mobile cellular networks: a semi-Markov process approach
verfasst von
Hee-Seon Jang
Jang Hyun Baek
Publikationsdatum
03.02.2021
Verlag
Springer US
Erschienen in
The Journal of Supercomputing / Ausgabe 8/2021
Print ISSN: 0920-8542
Elektronische ISSN: 1573-0484
DOI
https://doi.org/10.1007/s11227-021-03624-8

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