Abstract
This article presents a novel transmission power assignment mechanism for on-body wireless links formed between severely energy-constrained wearable and implanted sensors. The key idea is to develop a measurement-based framework in which the postural position as it pertains to a given wireless link is first inferred based on the measured RF signal strength and packet drops. Then optimal power assignment is done by fitting those measurement results into a model describing the relationship between the assigned power and the resulting signal strength. A closed loop power control mechanism is then added for iterative convergence to the optimal power level as a response to both intra-and-inter posture body movements. This provides a practical paradigm for on-body power assignment, which cannot leverage the existing mechanisms in the literature that rely on localization, which is not realistic for on-body sensors. Extensive experimental results are provided to demonstrate the model building and algorithm performance on a prototype body area network. The proposed mechanism has also been compared with a number of other closed loop mechanisms and an experimental benchmark.
- Agarwal, S., Krishnamurthy, S. V., Katz, R. H., and Dao, S. K. 2001. Distributed power control in ad hoc wireless networks. In Proceedings of the IEEE International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC).Google Scholar
- Bao, S., Zhang, Y., and Shen, L. 2005. Physiological signal based entity authentication for body area sensor networks and mobile healthcare systems. In Proceedings of the 27th IEEE Conference on Engineering in Medicine and Biology. 2455--2458.Google Scholar
- Chen, K. Y. and Bassett, D. R. 2005. The technology of accelerometry-based activity monitors: current and future. Med Sci Sports Exerc 37, 11, S490--S500.Google Scholar
Cross Ref
- Chipcon. http://www.chipcon.com/files/CC1000_Data_Sheet_2_1.pdf.Google Scholar
- Choi, S., Song, S. J., Sohn, K., Kim, H., Kim, J., Yoo, J., and Yoo, H. J. 2006. A low-power star-topology body area network controller for periodic data monitoring around and inside the human body. In Proceedings of the International Semantic Web Conference (ISWC), 139--140.Google Scholar
- Grants2. http://grants2.nih.gov/grants/guide/pa-files/PA-07-354.htmlGoogle Scholar
- Jovanov, E., Milenkovic, A., Otto, C., and De Groen, P. C. 2005a. A wireless body area network of intelligent motion sensors for computer assisted physical rehabilitation. J. Neuro Engin. Rehab. 2, 11, 6.Google Scholar
Cross Ref
- Jovanov, E., Milenković, A., Otto, C., De Groen, P., Johnson, B., Warren, S., and Taibi, G. 2005b. A WBAN system for ambulatory monitoring of physical activity and health status: applications and challenges, In Proc. of the Annual 3810--3.Google Scholar
- Klee, U., Gehrig, T., and Mcdonough, J. 2005. Kalman filters for time delay of arrival-based source localization. In Proceedings of the International Conference On Spoken Language Processing (INTERSPEECH), 2289--2292.Google Scholar
- Lee, S.-W. and Mase, K. 2002. Activity and location recognition using wearable sensors. Perv. Comput. 1, 3, 24--32. Google Scholar
Digital Library
- Lim, T. L. and Mohan, G. 2005. Energy aware geographical routing and topology control to improve network lifetime in wireless sensor networks Broadband Networks. In Proceedings of the 2nd International Global Telecommunications Conference. 829--831.Google Scholar
- Lin, S., Zhang, J., Zhou, G., Gu, L., Stankovic, J. A., and He, T. 2006. ATPC: Adaptive transmission power control for wireless sensor networks. In Proceedings of the 4th International Conference on Embedded Networked Sensor Systems. Google Scholar
Digital Library
- Liu, J. and Li, B. 2003. Distributed topology control in wireless sensor networks with asymmetric links. In Proceedings of IEEE Global Telecommunications Conference (GLOBECOM). 1257--1262.Google Scholar
- Lo, B., Thiemjarus, S., King, R., and Yang, G. 2005. Body sensor network—A wireless sensor platform for pervasive healthcare monitoring. In Proceedings of the 3rd International Conference on Pervasive Computing (PERVASIVE). 77--80.Google Scholar
- Lopez-Aguilera, E. and Casademont, J. 2006. A transmit power control proposal for IEEE 802.11 cellular networks. In Proceedings of 6th International Workshop on Applications and Services in Wireless Networks. 235--242.Google Scholar
- Milenkovic, A., Otto, C., and Jovanov, E. 2006. Wireless sensor networks for personal health monitoring: Issues and an implementation. Comp. Comm. (Special Issue: Wireless Sensor Networks: Performance, Reliability, Security, and Beyond), Elsevier. Google Scholar
Digital Library
- Moh, M., Culpepper, B., Dung, L., Moh, T.-S., Hamada, T., and Su, C.-F. 2005. On data gathering protocols for in-body biomedical sensor networks. In Proceedings of the 48th IEEE Global Telecommunications Conference (GlobeCom).Google Scholar
- Nar, P.C. and Cayirci E. 2005. PCSMAC: A power controlled sensor—MAC protocol for wireless sensor networks. In Proceedings of the 2nd European Workshop on Wireless Sensor Networks. 81--92.Google Scholar
- Norgall, T. 2005. Body area network—a key infrastructure element for patient-centric health services. In Proceeding of the Joint ISO TC215/WG7/IEEE 1073 Meeting.Google Scholar
- Otto, C., Milenkovic, A., Sanders, C., and Jovanov, E. 2006. System architecture of a wireless body area sensor network for ubiquitous health monitoring. J. Mobile Multimedia, 1, 4, 307--326. Google Scholar
Digital Library
- Qiao, D., Choi, S., Jain, A., and Shin, K. G. 2003. Adaptive transmit power control in IEEE 802.11a wireless LANs. In Proceedings of IEEE Vehiculer Technology Conference (VTC).Google Scholar
- Quwaider, M. and Biswas, S. 2008a. Body posture identification using hidden markov model with wearable sensor networks. In Proceedings of ACM Conference On Body Area Networks (BodyNets). Google Scholar
Digital Library
- Quwaider, M. and Biswas, S. 2008b. Physical context detection using multi-modal sensing using wearable wireless networks. J. Comm. Softw. Sys., Special Issue on Medical Applications for Wireless Sensor Networks, 4, 3, 191--202.Google Scholar
- Rintamaki, M. 2002. Power control in CDMA cellular communication, systems. In Wiley Encyclopedia of Telecommunications, J. G. Proakis, Ed., Wiley, New York.Google Scholar
- Rintamaki, M., Koivo, H., and Hartimo, I. 2004. Adaptive closed-loop power control algorithms for CDMA cellular communication systems. IEEE Trans. Vehic Tech., 53, 6.Google Scholar
Cross Ref
- Saghaei, H., and Neyestanak, A. 2007. Variable step closed-loop power control in cellular wireless CDMA systems under multipath fading. Comm. Comput. Signal Proc.Google Scholar
- Xbow. http://www.xbow.comGoogle Scholar
- Xiao, S., Sivaraman, V., and Burdett, A. 2008. Adapting radio transmit power in wireless body area sensor networks. In Proceedings of ACM Conference on Body Area Networks (BodyNets'08). Google Scholar
Digital Library
- Xing, G., Lu, C., and Pless, R. 2007. Localized and configurable topology control in lossy wireless sensor networks. In Proceedings of the International Conference on Computer Communications and Networks (ICCCN). 75--80.Google Scholar
- Zhou, G., He, T., Krishnamurthy, S., and Stankovic, J. A. 2004. Impact of radio irregularity on wireless sensor networks. In Proceedings of the 2nd International Conference on Mobile Systems, Applications, and Services. Google Scholar
Digital Library
Index Terms
Transmission power assignment with postural position inference for on-body wireless communication links
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