A Link Quality Estimator for Power-Efficient Communication over On-Body Channels
| dc.contributor.author | Recas Piorno, Joaquín | |
| dc.contributor.author | Ayala Rodrigo, José Luis | |
| dc.contributor.author | Vallejo, Mónica | |
| dc.date.accessioned | 2023-06-19T14:56:20Z | |
| dc.date.available | 2023-06-19T14:56:20Z | |
| dc.date.issued | 2014 | |
| dc.description.abstract | The human body has an important effect on the performance of on-body wireless communication systems. Given the dynamic and complex nature of the on-body channels, link quality estimation models are crucial in the design of mobility management protocols and power control protocols. In order to achieve a good estimation of link quality in WBSNs, we combine multiple body-related factors into a model that includes: the transmission power, the body position, the body shape and composition characteristics and the received signal strength indicator (RSSI) as an indicator of link quality. In this paper, we propose the Anfis Link Quality Estimator (A-LQE) that has been trained with RSSI values measured at different transmission power levels in a sample of 37 human subjects. Once the accuracy and reliability of our proposed model have been analysed, we apply the model to adapt the transmission power to the link characteristics for energy optimization. The obtained average energy savings reach the 26% in comparison with the maximum transmission power mode. | |
| dc.description.department | Depto. de Arquitectura de Computadores y Automática | |
| dc.description.faculty | Fac. de Informática | |
| dc.description.refereed | TRUE | |
| dc.description.sponsorship | Ministerio de Economía y Competitividad (MINECO) | |
| dc.description.sponsorship | COLCIENCIAS | |
| dc.description.sponsorship | Universidad Nacional de Colombia | |
| dc.description.status | pub | |
| dc.eprint.id | https://eprints.ucm.es/id/eprint/33198 | |
| dc.identifier.doi | 10.1109/EUC.2014.44 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14352/34871 | |
| dc.journal.title | Proceedings - 2014 International Conference on Embedded and Ubiquitous Computing, EUC 2014 | |
| dc.language.iso | eng | |
| dc.page.final | 257 | |
| dc.page.initial | 250 | |
| dc.relation.projectID | TIN2008-00508 | |
| dc.relation.projectID | TEC2012-33892 | |
| dc.rights.accessRights | open access | |
| dc.subject.cdu | 004 | |
| dc.subject.keyword | WBSNs | |
| dc.subject.keyword | On-body channels | |
| dc.subject.keyword | Link quality estimator | |
| dc.subject.keyword | Transmission power control | |
| dc.subject.keyword | Energy savings | |
| dc.subject.ucm | Informática (Informática) | |
| dc.subject.unesco | 1203.17 Informática | |
| dc.title | A Link Quality Estimator for Power-Efficient Communication over On-Body Channels | |
| dc.type | journal article | |
| dcterms.references | [1] C. F. García-Hernández, P. H. Ibarguengoytia-Gonzalez, J. García-Hernández, and J. A. Pérez-Díaz, “Wireless sensor networks and applications: a survey,” IJCSNS International Journal of Computer Science and Network Security, vol. 7, no. 3, pp. 264–273, 2007. [2] A. Dhamdhere, V. Sivaraman, V. Mathur, and S. Xiao, “Algorithms for transmission power control in biomedical wireless sensor networks,” in Asia-Pacific Services Computing Conference, 2008. APSCC’08. IEEE. IEEE, 2008, pp. 1114– 1119. [3] S. Xiao, A. Dhamdhere, V. Sivaraman, and A. Burdett, “Transmission power control in body area sensor networks for healthcare monitoring,” Selected Areas in Communications, IEEE Journal on, vol. 27, no. 1, pp. 37–48, 2009. [4] F. Di Franco, C. Tachtatzis, B. Graham, M. Bykowski, D. C. Tracey, N. F. Timmons, and J. Morrison, “The effect of body shape and gender on wireless body area network on-body channels,” in Antennas and Propagation (MECAP), 2010 IEEE Middle East Conference on. IEEE, 2010, pp. 1–3. [5] R. Fonseca, O. Gnawali, K. Jamieson, and P. Levis, “Fourbit wireless link estimation,” in Proceedings of the Sixth Workshop on Hot Topics in Networks (HotNets VI), vol. 2007, 2007. [6] M. Senel, K. Chintalapudi, D. Lal, A. Keshavarzian, and E. J. Coyle, “A kalman filter based link quality estimation scheme for wireless sensor networks,” in Global Telecommunications Conference, 2007. GLOBECOM’07. IEEE. IEEE, 2007, pp. 875–880. [7] I. Fernández Anitzine, J. A. Romo Argota, and F. P. Fontán, “Influence of training set selection in artificial neural networkbased propagation path loss predictions,” International Journal of Antennas and Propagation, vol. 2012, 2012. [8] T. Liu and A. E. Cerpa, “Foresee (4c): Wireless link prediction using link features,” in Information Processing in Sensor Networks (IPSN), 2011 10th International Conference on. IEEE, 2011, pp. 294–305. [9] Q. Tang, N. Tummala, S. K. Gupta, and L. Schwiebert, “Communication scheduling to minimize thermal effects of implanted biosensor networks in homogeneous tissue,” Biomedical Engineering, IEEE Transactions on, vol. 52, no. 7, pp. 1285–1294, 2005. [10] S. Kim and D.-S. Eom, “Rssi/lqi-based transmission power control for body area networks in healthcare environment,” 2012. [11] M. Vallejo, J. Recas, P. G. del Valle, and J. L. Ayala, “Accurate human tissue characterization for energy-efficient wireless on-body communications,” Sensors, vol. 13, no. 6, pp. 7546–7569, 2013. [12] I. Research, “Shimmer wbsn platform.” http://www.shimmerresearch.com. [13] C. Corporation, “Cc2420 2.4 ghz ieee 802.15.4 / zigbee-ready rf transceiver.” http://www.ti.com/lit/gpn/cc2420. [14] “Bc-601f fitscan segmental body composition monitor,” http://www.tanita.com/en/bc601f/. [15] J.-S. Jang, “Anfis: adaptive-network-based fuzzy inference system,” Systems, Man and Cybernetics, IEEE Transactions on, vol. 23, no. 3, pp. 665–685, 1993. [16] R. Jang, C. Sun, and E. Mizutani, “Neuro-fuzzy and soft computation,” 1997. [17] T. Nuguyen, C. Walker, and E. Walker, “A first course in fuzzy and neural control,” Boca Raton, FL, 2003. [18] M. Sugeno, Industrial applications of fuzzy control. Elsevier Science Inc., 1985. [19] S. L. Chiu, “Selecting input variables for fuzzy models,” Journal of Intelligent and Fuzzy Systems-Applications in Engineering and Technology, vol. 4, no. 4, pp. 243–256, 1996. [20] M. Hosoz, H. Ertunc, and H. Bulgurcu, “Performance prediction of a cooling tower using artificial neural network,” Energy Conversion and Management, vol. 48, no. 4, pp. 1349–1359, 2007. [21] T. Nazmy, H. El-Messiry, and B. Al-Bokhity, “Adaptive neuro-fuzzy inference system for classification of ecg signals,” in Informatics and Systems (INFOS), 2010 The 7th International Conference on. IEEE, 2010, pp. 1–6. | |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 8e1e37da-1ec8-4b19-add3-20bbf6cb971c | |
| relation.isAuthorOfPublication | d73a810d-34c3-440e-8b5f-e2a7b0eb538f | |
| relation.isAuthorOfPublication.latestForDiscovery | 8e1e37da-1ec8-4b19-add3-20bbf6cb971c |
Download
Original bundle
1 - 1 of 1
