An Experimental Study for Inter-User Interference Mitigation in Wireless Body Sensor Networks

• Main Authors: CAO, Bin, GE, Yu, KIM, Chee Wee, FENG, Gang, TAN, Hwee-Pink, LI, Yun
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2013
• Subjects: Wireless body sensor network; IEEE 802.15.4; interference mitigation; experimental study; hopping mechanism; Computer and Systems Architecture; Software Engineering
• Online Access: https://ink.library.smu.edu.sg/sis_research/2961; https://ink.library.smu.edu.sg/context/sis_research/article/3961/viewcontent/IEEESensors2013.pdf
• Institution: Singapore Management University

Inter-user interference degrades the reliability of data delivery in wireless body sensor networks (WBSNs) in dense deployments when multiple users wearing WBSNs are in close proximity to one another. The impact of such interference in realistic WBSN systems is significant but is not well explored. To this end, we investigate and analyze the impact of inter-user interference on packet delivery ratio (PDR) and throughput. We conduct extensive experiments based on the TelosB WBSN platform, considering unslotted carrier sense multiple access (CSMA) with collision avoidance (CA) and slotted CSMA/CA modes in IEEE 802.15.4 MAC, respectively. In order to mitigate interuser interference, we propose a light-weight hopping approach based on practical WBSN systems and investigate the performance in a realistic environment. Our experimental results show that the unslotted CSMA/CA is only effective in light inter-user interference scenarios. Comparably, the slotted CSMA/CA can provide dramatic performance improvement (2.7 times higher in PDR and 1.7 times higher in throughput on average), when severe inter-user interference occurs in WBSN deployment. In addition, the experimental results validate the effectiveness and correctness of our idea of a hopping approach for inter-user interference mitigation, which is based on slotted CSMA/CA mode and with low complexity.