Presentation 1998/2/6
A neural network for channel assignment problem in cellular mobile communication system
Takuya Tamura, Kunio Oishi, Shoichiro Yamaguchi,
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Abstract(in English) This paper presents channel assignment algorithms for cellular mobile communication system. When we are planning this system, the system has to assign frequencies to the cells. The problem has to satisfy a total of user calls with minimizing interference in the co-site constraint, the cochannel constraint, and the adjacent channel constraint. This problem is NP-complete, and an exact search for the best channel assignment is practically impossible due to an exponentially growing calculation time. Since Funabiki, et al. [5] proposed the parallel neural network algorithms. But the algorithm can not always find the global minima solution. In this paper, we propose neural networks that the advantage of the improved model resolve the issue of interference in detail. The simulation results show that the improved neural network finds the better channel assignment pattern.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) Neural network / Channel assignment / Cellular model / Mobile communication system
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Conference Information
Committee NLP
Conference Date 1998/2/6(1days)
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Paper Information
Registration To Nonlinear Problems (NLP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A neural network for channel assignment problem in cellular mobile communication system
Sub Title (in English)
Keyword(1) Neural network
Keyword(2) Channel assignment
Keyword(3) Cellular model
Keyword(4) Mobile communication system
1st Author's Name Takuya Tamura
1st Author's Affiliation Systems Electronics, Tokyo Engineering University Graduate School()
2nd Author's Name Kunio Oishi
2nd Author's Affiliation Department of Electronics, Faculty of Engineerign, Tokyo Engineering University
3rd Author's Name Shoichiro Yamaguchi
3rd Author's Affiliation Systems Electronics, Tokyo Engineering University Graduate School
Date 1998/2/6
Paper #
Volume (vol) vol.97
Number (no) 531
Page pp.pp.-
#Pages 8
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