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A Joint Transmission Power Control and Duty-Cycle Approach for Smart Healthcare System
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering. Electrical Engineering Department Sukkur IBA, Pakistan.ORCID iD: 0000-0001-5502-530X
CAS, SIAT, Shenzhen, China .
Physics Shah Abdul Latif, Pakistan .
Linköping University, Department of Computer and Information Science, Database and information techniques. Linköping University, Faculty of Science & Engineering.ORCID iD: 0000-0002-9829-9287
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2019 (English)In: IEEE Sensors Journal, ISSN 1530-437X, E-ISSN 1558-1748, Vol. 19, no 19, p. 8479-8486Article in journal (Refereed) Published
Abstract [en]

Emerging revolution in the healthcare has caught the attention of both the industry and academia due to the rapid proliferation in the wearable devices and innovative techniques. In the mean-time, Body Sensor Networks (BSNs) have become the potential candidate in transforming the entire landscape of the medical world. However, large battery lifetime and less power drain are very vital for these resource-constrained sensor devices while collecting the bio-signals. Hence, minimizing their charge and energy depletions are still very challenging tasks. It is examined through large real-time data sets that due to the dynamic nature of the wireless channel, the traditional predictive transmission power control (PTPC) and a constant transmission power techniques are no more supportive and potential candidates for BSNs. Thus this paper first, proposes a novel joint transmission power control (TPC) and duty-cycle adaptation based framework for pervasive healthcare. Second, adaptive energy-efficient transmission power control (AETPC) algorithm is developed by adapting the temporal variation in the on-body wireless channel amid static (i.e., standing and walking at a constant speed) and dynamic (i.e., running) body postures. Third, a Feedback Control-based duty-cycle algorithm is proposed for adjusting the execution period of tasks (i.e., sensing and transmission). Fourth, system-level battery and energy harvesting models are proposed for body sensor nodes by examining the energy depletion of sensing and transmission tasks. It is validated through Monte Carlo experimental analysis that proposed algorithm saves more energy of 11.5% with reasonable packet loss ratio (PLR) by adjusting both transmission power and duty-cycle unlike the conventional constant TPC and PTPC methods.

Place, publisher, year, edition, pages
IEEE, 2019. Vol. 19, no 19, p. 8479-8486
Keywords [en]
Duty-cycle;Body Posture;Smart Healthcare;energy harvesting;AETPC;BSN;PTPC;Constant TPC
National Category
Computer Engineering
Identifiers
URN: urn:nbn:se:liu:diva-153119DOI: 10.1109/JSEN.2018.2881611ISI: 000487216200014OAI: oai:DiVA.org:liu-153119DiVA, id: diva2:1266565
Note

This work is done under the supervision of Prof. Andrei Gurtov

Available from: 2018-11-28 Created: 2018-11-28 Last updated: 2019-11-04

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Sodhro, Ali HassanGurtov, Andrei

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