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A Multi-Radio Interface for Dependable Body Area Network Communications

Body Area Networks (BANs) are emerging as a convenient option for patient monitoring. They have shown potential in improving health care services through a network of external or implanted biosensors and actuators collecting real-time physiological data. Advancements in wireless networking and sensor development are expediting the adoption of BANs. However, real-time patient monitoring still remains a challenge due to network failures and congestion. In order to improve channel loss resilience and thus link availability, a multi-radio systems approach is adopted incorporating Bluetooth and Wi-Fi.

In this work, we propose a multi-radio interface designed for a BAN to improve end-to-end communications. A multi-radio BAN controller is introduced to interface between the two wireless protocols (Wi-Fi and Bluetooth), control inter-radio handovers, manage a shared transmission buffer, and overall, route data accordingly through the protocol stacks. Simulations are conducted to study the performance of the system by adjusting handover timing and its effect on link availability. Advancing a handover has the benefit of a higher throughput at the cost of an increase in power consumption and timing overhead. Furthermore, various human mobility models, AP placement arrangements, and network densities are simulated to evaluate the performance of the BAN multi-radio interface. Sparse networks were found to have the most gain from the addition of the secondary Bluetooth radio system, as primary AP coverage was already very limited. Simulation results for various combinations of simulation parameters are presented to illustrate the improvement in BAN dependability through a multi-radio interface.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:OWTU.10012/6515
Date01 1900
CreatorsHovakeemian, Yasmin
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis or Dissertation

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