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Kazuhiko SHIMADA Keisuke NAKANO Masakazu SENGOKU Takeo ABE
In cellular mobile systems, an alternative approach for a Dynamic Channel Assignment problem is presented. It adaptively assigns the channels considering the cochannel interference level. The Dynamic Channel Assignment problem is modeled on the different cellular system from the conventional one. In this paper, we formulate the rearrangement problem in the Dynamic Channel Assignment and propose a novel strategy for the problem. The proposed algorithm is based on an artificial neural network as a specific dynamical system, and is successfully applied to the cellular system models. The computer simulation results show that the algorithm utilized for the rearrangement is an effective strategy to improve the traffic characteristics.
Kazuhiko SHIMADA Takeshi WATANABE Masakazu SENGOKU Takeo ABE
The applicability of Dynamic Channel Assignment methods to a Reuse Partitioning system in cellular radio systems is investigated in this paper. The investigations indicate that such a system has a tendency to increase the difference between blocking probability for the partitioning two coverage areas in comparison with the conventional Reuse Partitioning system employing Fixed Channel Assignment method. Two schemes using new Channel Rearrangement algorithms are also proposed in order to alleviate the difference as a disadvantage which gives unequal service to the system. The simulation results show that the proposed schemes are able to reduce the difference significantly while increasing the carried traffic by 10% as compared with the conventional system.
Kazuhiko SHIMADA Masakazu SENGOKU Takeo ABE
A novel algorithm, as an advanced Hybrid Channel Assignment strategy, for channel assignment problem in a cellular system is proposed. A difference from the conventional Hybrid Channel Assignment method is that flexible fixed channel allocations which are variable through the channel assignment can be performed in order to cope with varying traffic. This strategy utilizes the Channel Rearrangement technique using the artificial neural network algorithm in order to enhance channel occupancy on the fixed channels. The strategy is applied to two simulation models which are the spatial homogeneous and inhomogeneous systems in traffic. The simulation results show that the strategy can effectively improve blocking probability in comparison with pure dynamic channel assignment strategy only with the Channel Rearrangement.