A Prediction Algorithm for Coexistence Problem in Multiple-WBAN Environment. (16th March 2015)

• Record Type: Journal Article
• Authors: Jin, Zilong; Han, Yoonjeong; Cho, Jinsung; Lee, Ben
• Other Names: Staiano Antonino Academic Editor.
• Is Part Of: International journal of distributed sensor networks. (2015)
• Publication Date: 2015-03-16
• Subjects: Sensor networks -- Periodicals; Intelligent agents (Computer software) -- Periodicals; Multisensor data fusion -- Periodicals; 681.2
• DOI: 10.1155/2015/386842
• Languages: English
• ISSNs: 1550-1329

Abstract

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.