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ACESS: Adaptive Channel Estimation and Selection Scheme for Coexistence Mitigation in WBANs

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Published:04 January 2016Publication History

ABSTRACT

A Wireless Body Area Networks (WBAN) is a communication network that provides both medical and consumer electronics (CE) services by using sensor devices in, on, or around a human body. To provide reliable communication with low power consumption for in-body communication, the IEEE 802.15.6 provides Medical Implant Communication Service (MICS) band and defines its communication policy. However, MICS band communication suffer from the coexistence problem, which causes significant performance degradation due to high-density deployment and network-level mobility of WBANs. In addition, existing coexistence mitigation schemes in IEEE 802.15.6 do not consider the MICS band. To overcome the coexistence problem, numerous studies have been conducted for multi-channel usage in WBANs, but they just include simple channel selection schemes which do not provide reliable channel selection. This paper proposes an Adaptive Channel Estimation and Selection Scheme (ACESS) for coexistence mitigation in WBANs. The proposed method maintains a history table and predicts the conditions of available channels based on two-state Markov chain with an exponentially controlled channel history, which can control the sensitivity of prediction. Our simulation study show that the proposed scheme can improve communication performance in terms of Packet Reception Ratio (PRR) under coexistence environments with multiple WBANs.

References

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  1. ACESS: Adaptive Channel Estimation and Selection Scheme for Coexistence Mitigation in WBANs

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    • Published in

      cover image ACM Conferences
      IMCOM '16: Proceedings of the 10th International Conference on Ubiquitous Information Management and Communication
      January 2016
      658 pages
      ISBN:9781450341424
      DOI:10.1145/2857546

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      Publication History

      • Published: 4 January 2016

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      Overall Acceptance Rate213of621submissions,34%

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