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A Prediction Algorithm for Coexistence Problem in Multiple-WBAN Environment

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Listed:
  • Zilong Jin
  • Yoonjeong Han
  • Jinsung Cho
  • Ben Lee

Abstract

The coexistence problem occurs when a single wireless body area network (WBAN) is located within a multiple-WBAN environment. This causes WBANs to suffer from severe channel interference that degrades the communication performance of each WBAN. Since a WBAN handles vital signs that affect human life, the detection or prediction of coexistence condition is needed to guarantee reliable communication for each sensor node of a WBAN. Therefore, this paper presents a learning-based algorithm to efficiently predict the coexistence condition in a multiple-WBAN environment. The proposed algorithm jointly applies PRR and SINR, which are commonly used in wireless communication as a way to measure the quality of wireless connections. Our extensive simulation study using Castalia 3.2 simulator based on the OMNet++ platform shows that the proposed algorithm provides more reliable and accurate prediction than existing methods for detecting the coexistence problem in a multiple-WBAN environment.

Suggested Citation

  • Zilong Jin & Yoonjeong Han & Jinsung Cho & Ben Lee, 2015. "A Prediction Algorithm for Coexistence Problem in Multiple-WBAN Environment," International Journal of Distributed Sensor Networks, , vol. 11(3), pages 386842-3868, March.
    • Handle: RePEc:sae:intdis:v:11:y:2015:i:3:p:386842
    DOI: 10.1155/2015/386842
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