Abstract
As an important coexistence technology, channel hopping can reduce the interference among Wireless Body Area Networks (WBANs). However, it simultaneously brings some issues, such as energy waste, long latency and communication interruptions, etc. In this paper, we propose an enhanced channel hopping mechanism that allows multiple WBANs coexisted in the same channel. In order to evaluate the coexistence performance, some critical metrics are designed to reflect the possibility of channel conflict. Furthermore, by taking the queuing and non-queuing behaviors into consideration, we present a set of analysis approaches to evaluate the coexistence capability. On the one hand, we present both service-dependent and service-independent analysis models to estimate the number of coexisting WBANs. On the other hand, based on the uniform distribution assumption and the additive property of Possion-stream, we put forward two approximate methods to compute the number of occupied channels. Extensive simulation results demonstrate that our estimation approaches can provide an effective solution for coexistence capability estimation. Moreover, the enhanced channel hopping mechanism can significantly improve the coexistence capability and support a larger arrival rate of WBANs.
Highlights
Biomedical sensors, motion sensors, and other wearable devices are usually deployed on, near, or in human bodies to monitor vital signals (e.g., ECG, EEG, EMG, blood oxygen, blood glucose, blood pressure and heart rate) or non-medical signals (e.g., GPS, acceleration and rotation)
A basic property should be taken into account before we investigate the coexistence capability of the enhanced channel hopping mechanism under 1-tolerated channel conflict model, referred to Property 1
According to IEEE 802.15.6, which specifies different number of channels (10, 12, 14, 16, 39, 60, 79) for coexisting Wireless Body Area Networks (WBANs), we employ the worst case for coexistence capability studies, i.e., n = 10
Summary
Biomedical sensors, motion sensors, and other wearable devices are usually deployed on, near, or in human bodies to monitor vital signals (e.g., ECG, EEG, EMG, blood oxygen, blood glucose, blood pressure and heart rate) or non-medical signals (e.g., GPS, acceleration and rotation). These wearable devices networking together forms Wireless Body Area Networks (WBANs), which are the most promising technologies in many rising and interesting applications, such as remote health care, sports, and entertainment [1,2,3,4,5]. Coexistence of multiple WBANs is an inherent and severe challenge due to natural mobility of human beings [6].
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