Cognitive Wireless Sensor Networks: Intelligent Channel Assignment

  • Soamsiri Chantaraskul The SirindhornInternational Thai-German Graduate School of Engineering (TGGS)
  • Chayaphon Tanwongvarl The SirindhornInternational Thai-German Graduate School of Engineering (TGGS)
Keywords: Wireless sensor networks, cognitive radio, channel assignment, policy gradient.

Abstract

One of the major problems in Wireless Sensor Networks (WSNs) is the traffic congestion caused by increasing number of devices sharing the limited spectrum of the ISM (Industrial, Scientific, and Medical radio) band. As a result, a new concept of Cognitive Wireless Sensor Networks (CWSNs) has been proposed in order to achieve reliable and efficient communication via spectrum awareness and smart adaption. Based on such concept, this paper proposes the intelligent channel assignment technique for channel management in CWSNs. The proposed method is based on the learning and prediction technique so called Policy Gradient together with our proposed virtual channel environment classification. Simulation model is used for the system performance evaluation. The simulation results show that our proposed intelligent channel assignment provides substantially higher performance in terms of system throughput and average packet end-to-end delay than the traditional IEEE 802.15.4 based system. It also outperforms the systems integrated with Episodic Reinforcement and GPOMDP learning technique.

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Author Biographies

Soamsiri Chantaraskul

The SirindhornInternational Thai-German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, 1518 Pibulsongkram Road, Bangsue, Bangkok, Thailand

Chayaphon Tanwongvarl

The SirindhornInternational Thai-German Graduate School of Engineering (TGGS), King Mongkut’s University of Technology North Bangkok, 1518 Pibulsongkram Road, Bangsue, Bangkok, Thailand

Published In
Vol 21 No 1, Jan 31, 2017
How to Cite
[1]
S. Chantaraskul and C. Tanwongvarl, “Cognitive Wireless Sensor Networks: Intelligent Channel Assignment”, Eng. J., vol. 21, no. 1, pp. 279-292, Jan. 2017.