ICTACT Journal on Communication Technology

Yee Shin Chia ¹, Zhan Wei Siew ¹, Hoe Tung Yew ¹, Soo Siang Yang ¹, Kenneth Tze Kin Teo ¹

Affiliations
1 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, MY

Abstract

The channel assignment problem in wireless mobile network is the assignment of appropriate frequency spectrum to incoming calls while maintaining a satisfactory level of electromagnetic compatibility (EMC) constraints. An effective channel assignment strategy is important due to the limited capacity of frequency spectrum in wireless mobile network. Most of the existing channel assignment strategies are based on deterministic methods. In this paper, an adaptive genetic algorithm (GA) based channel assignment strategy is introduced for resource management and to reduce the effect of EMC interferences. The most significant advantage of the proposed optimization method is its capability to handle both the reassignment of channels for existing calls as well as the allocation of channel to a new incoming call in an adaptive process to maximize the utility of the limited resources. It is capable to adapt the population size to the number of eligible channels for a particular cell upon new call arrivals to achieve reasonable convergence speed. The MATLAB simulation on a 49-cells network model for both uniform and nonuniform call traffic distributions showed that the proposed channel optimization method can always achieve a lower average new incoming call blocking probability compared to the deterministic based channel assignment strategy.

Keywords

Evolutionary Optimization, Genetic Algorithm, Hybrid Channel Assignment, Wireless Mobile Network.

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Zhan Wei Siew ¹, Chen How Wong ¹, Aroland Kiring ¹, Renee Ka Yin Chin ¹, Kenneth Tze Kin Teo ²

Affiliations
1 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, MY
2 Modeling, Simulation & Computing Laboratory, Material & Mineral Research Unit School of Engineering and Information Technology, Universiti Malaysia Sabah, MY

Abstract

Wireless sensor networks (WSNs) have been vastly developed due to the advances in microelectromechanical systems (MEMS) using WSN to study and monitor the environments towards climates changes. In environmental monitoring, sensors are randomly deployed over the interest area to periodically sense the physical environments for a few months or even a year. Therefore, to prolong the network lifetime with limited battery capacity becomes a challenging issue. Low energy adaptive cluster hierarchical (LEACH) is the common clustering protocol that aim to reduce the energy consumption by rotating the heavy workload cluster heads (CHs). The CHs election in LEACH is based on probability model which will lead to inefficient in energy consumption due to least desired CHs location in the network. In WSNs, the CHs location can directly influence the network energy consumption and further affect the network lifetime. In this paper, factors which will affect the network lifetime will be presented and the demonstration of fuzzy logic based CH selection conducted in base station (BS) will also be carried out. To select suitable CHs that will prolong the network first node dies (FND) round and consistent throughput to the BS, energy level and distance to the BS are selected as fuzzy inputs.

Keywords

Wireless Sensor Network, Cluster Head, First Node Dies, Fuzzy Logic.

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