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Artificial intelligence‐based novel scheme for location area planning in cellular networks
Author(s) -
Vimal Vrince,
Singh Teekam,
Qamar Shamimul,
Nautiyal Bhaskar,
Udham Singh Kamred,
Kumar Abhishek
Publication year - 2021
Publication title -
computational intelligence
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.353
H-Index - 52
eISSN - 1467-8640
pISSN - 0824-7935
DOI - 10.1111/coin.12371
Subject(s) - paging , computer science , scheme (mathematics) , cellular network , total cost , service (business) , computer network , mathematical optimization , mathematics , economy , economics , microeconomics , mathematical analysis
Planning of location area (LA) in cellular networks plays a vital role in utilizing the resources efficiently and economically. Location update and paging costs directly affect the cost to the service provider. When the size of the Mobile Switching Centre (MSC) is large, the paging cost becomes maximum. Though, no location update is required for this case. On the contrary, paging cost shoots high if each cell forms individual LA, but in this case, location update cost shoots to the maximum value. Therefore, deducing the network to the optimal amount of LA's is an intractable combinatorial optimization problem. In this paper, we intend to optimize the partitions of the MSC service area into an optimal number of LA, to curtail the total location management cost. We propose a novel scheme bearing in mind cell attributes of the network to deduce an optimum number of location areas, leading to minimum cost per call. It is revealed by the results of this work, attained after simulating the scenario on MATLAB 2018a that Cell Attributes Based Algorithm is a very promising scheme for cellular networks, and it outperforms the existing algorithms in a practical scenario.