Energy efficiency evaluation of the pulse shapes and modulation techniques for IR-UWB in WBANs

Avila, Leandro; Kunst, Rafael; Pignaton, Edison; Rochol, Juergen; Bampi, Sérgio

doi:10.1109/icecs.2016.7841160

Cited by 6 publications

(1 citation statement)

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“…Various UWB channel models have been investigated. [17][18][19] Generally speaking, for a wireless body sensor network, the signal arrives at the receiver node in three ways:…”

Section: Body Channel Modelmentioning

confidence: 99%

Internet of Things ‐ integrated IR‐UWB technology for healthcare applications

Chehri

Mouftah

2019

Concurrency and Computation

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Summary Recent technology developments have produced small and smart biomedical sensors, which can be worn or implanted in the human body. These biosensors create closed wireless networks named Wireless Body Area Networks (WBAN). The WBAN will continuously observe the physiological state of patients for both diagnosis and prevention. Those include on‐body measurements such as the Electrocardiogram (ECG), Electroencephalogram (EEG), temperature, and blood pressure. Ultra‐Wide‐Band (UWB) is a technology that has received a lot of attention due to several unique features such as secure transmission, low noise, and low energy consumption. Given the fact that the patients' well‐being might be dependent on the accurate realization of such networks, a high level of design and implementation accuracy are maintained throughout the system. In this paper, we proposed an Impulse‐Radio Ultra‐Wideband system, which is composed of static biomedical nodes mounted on a patient's body to collect vital data and send it wirelessly to a central node or subsequent analysis by healthcare professionals. The performance of this network, such as the effect of node location, the number of transmitted symbols, multiuser interference, and intersymbol interference, is evaluated. We also study the physical layer and quality of service of this proposed architecture.

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“…Various UWB channel models have been investigated. [17][18][19] Generally speaking, for a wireless body sensor network, the signal arrives at the receiver node in three ways:…”

Section: Body Channel Modelmentioning

confidence: 99%