2013 IEEE 11th Malaysia International Conference on Communications (MICC) 2013
DOI: 10.1109/micc.2013.6805848
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Performance investigation of opportunistic routing using log-normal and IEEE 802.15.6 CM 3A path loss models in WBANs

Abstract: Wireless Body Area Network (WBAN) is a modern technology having a wide range of possible applications. The development scope of WBANs can diverse from hardware and applications design to network performance optimization. Reliability is a vital performance factor in WBANs. Body shadowing, environmental interference and inefficient routing can make a WBAN unreliable, which may severely affect the patient under observation. However, an opportunistic routing technique can improve the reliability via multihops by u… Show more

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Cited by 11 publications
(3 citation statements)
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“…For this work, we consider the IEEE 802.15.6 Channel propagation Model 3A [55], where its performance analysis was also done in our earlier work in [56]. The mathematical description of this model is given as,…”
Section: A Comr For Wbansmentioning
confidence: 99%
“…For this work, we consider the IEEE 802.15.6 Channel propagation Model 3A [55], where its performance analysis was also done in our earlier work in [56]. The mathematical description of this model is given as,…”
Section: A Comr For Wbansmentioning
confidence: 99%
“…References [7] proposed a grey-FTPC algorithm using gray prediction and fuzzy inference, which used gray prediction to predict the channel state and then adjusted the transmission power according to the predicted value of the channel. Log Normal and IEEE 802.15.6 CM 3A path loss models were used in References [8] to evaluate similar opportunistic routing mechanisms.…”
Section: Introductionmentioning
confidence: 99%
“…The source node broadcasts an RTS packet and the contention is won by the relay node which randomly replies first. Authors have analyzed a SOR technique for WBANs in [15], [16]. This selection mechanism does not assure that the selected node will improve the reliability.…”
mentioning
confidence: 99%