Second-Order Statistics for Many-Link Body Area Networks

Chaganti, Vasanta; Smith, David B.; Hanlen, Leif

doi:10.1109/lawp.2010.2048690

Cited by 16 publications

(20 citation statements)

References 8 publications

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“…The first method collects data using a vector network analyzer measuring S21 between a transmitter on the body and a receiver (e.g. [41]). The second method records RSSI or LQI of a signal at a given sampling frequency (e.g.…”

Section: Exploiting Periodic or Predictable Wireless Channelsmentioning

confidence: 99%

“…[40]). Path loss models are generated using curve/distribution fitting while second order statistics such as amplitude distribution, level crossing rate, and fade duration are measured as well [41]. Distributions such as lognormal, Rayleigh, Weibull, and Gamma, are all found to be a best fit in certain situations, but the most common fit is lognormal.…”

Section: Exploiting Periodic or Predictable Wireless Channelsmentioning

confidence: 99%

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Body Sensor Networks: A Holistic Approach From Silicon to Users

et al. 2012

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Abstract-Body sensor networks (BSN) are emerging cyberphysical systems that promise to improve quality of life through improved healthcare, augmented sensing and actuation for the disabled, independent living for the elderly, and reduced healthcare costs. However, the physical nature of BSNs introduces new challenges. The human body is a highly dynamic physical environment that creates constantly changing demands on sensing, actuation, and quality of service. Movement between indoor and outdoor environments and physical movements constantly change the wireless channel characteristics. These dynamic application contexts can also have a dramatic impact on data and resource prioritization. Thus, BSNs must simultaneously deal with rapid changes to both top-down application requirements and bottom-up resource availability. This is made all the more challenging by the wearable nature of BSN devices, which necessitates a vanishingly small size and, therefore, extremely limited hardware resources and power budget. Current research is being performed to develop new principles and techniques for adaptive operation in highly dynamic physical environments, using miniaturized, energy-constrained devices. This paper describes a holistic cross-layer approach that addresses all aspects of the system, from low-level hardware design to higher-level communication and data fusion algorithms, to top-level applications.

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Section: Exploiting Periodic or Predictable Wireless Channelsmentioning

confidence: 99%

Section: Exploiting Periodic or Predictable Wireless Channelsmentioning

confidence: 99%

Body Sensor Networks: A Holistic Approach From Silicon to Users

et al. 2012

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“…Several theoretical distributions have been proposed to characterize the small-scale fading behaviour in on-body channels. In this study, we performed a statistical analysis of the measured data in order to extract the statistics of five theoretical models commonly used in on-body channel modeling studies [1]- [7], namely Nakagami-m, Rice, lognormal, gamma and Į-ȝ. These five distributions have been selected because they have successfully been used in the past to model the on-body channel in many related works.…”

Section: B On-body Channel Modelingmentioning

confidence: 99%

“…Among the commonly used fading distributions, the Nakagami-m has been found to provide a good fit to on-body channels in many related works [1], [2]. However, recently, several other distributions have been proposed to fit the on-body channel, such as Rice, lognormal, gamma and Į-ȝ [3]- [7]. The knowledge of the distribution of the on-body channel is useful for the calculation of performance metrics such as channel capacity and second order statistics.…”

Section: Introductionmentioning

confidence: 99%

Impact of channel modeling on accurate estimation of on-body channel capacity

Michalopoulou

Zervos

Peppas

et al. 2012

2012 6th European Conference on Antennas and Propagation (EUCAP)

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This paper investigates the impact of on-body channel modeling on the accurate estimation of BAN system performance. Channel capacity is used as a measure of the onbody system performance. The actual channel capacity is calculated based on signal measurements conducted in an indoor environment. Then it is compared to the channel capacity calculated for five theoretical channel models obtained through statistical analysis of the measured data. Body area network (BAN), on-body channel, channel modeling, channel capacity

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“…Especially, the collective-diagnosis in chronic patients can be greatly affected due to the disruption in communication caused by the interference of the human activities in the RF link. Impact of human activities on the RF spectrum has been studied before and it has been shown that each activity has its unique pattern regarding influencing the RF spectrum [8].…”

Section: Introductionmentioning

confidence: 99%

HACMAC: A reliable human activity-based medium access control for implantable body sensor networks

Ramachandran

Havinga

Meratnia

2016

2016 IEEE 13th International Conference on Wearable and Implantable Body Sensor Networks (BSN)

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Abstract-Chronic care is an eminent application of implantable body sensor networks (IBSN). Performing physical activities such as walking, running, and sitting is unavoidable during the long-term monitoring of chronic-care patients. These physical activities cripple the radio frequency (RF) signal between the implanted sensor nodes. This is because various body postures shadow the RF signal. Although shadowing itself may be short, a prolonged activity will significantly increase the effect of the RF-shadowing. This effect dampens the communication between implantable sensor nodes and hence increases the chance of missing life-critical data. To overcome this problem, in this paper we propose a link quality-aware medium access control (MAC) protocol called HACMAC, which adapts the access mechanism during different human activities based on the wireless link-quality. Our simulation results show that compared with the access mechanism suggested by the IEEE 802.15.6 standard, the reliability of the wireless communication is increased using HACMAC even while transmitting at a strongly low transmission power of 25µW effective isotropic radiated power (EIRP) set by the IEEE 802.15.6 standard.

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Second-Order Statistics for Many-Link Body Area Networks

Cited by 16 publications

References 8 publications

Body Sensor Networks: A Holistic Approach From Silicon to Users

Body Sensor Networks: A Holistic Approach From Silicon to Users

Impact of channel modeling on accurate estimation of on-body channel capacity

HACMAC: A reliable human activity-based medium access control for implantable body sensor networks

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