Motion aware transmission power control scheme in wireless body area network

Energy consumption is a key issue in wireless body area network (WBAN) since the wearable sensor devices are severely resource-constrained. In this paper, we present a novel transmission power control scheme, which exploit the regular body motion in dynamic wireless channel for WBAN. We first investigate the relationship between the link state and body movement with experiment, and give the evidence that the path loss is strongly related to the body movement. We then propose the motion aware transmission power control (M-TPC) scheme which takes advantage of the information from activity recognition algorithm and arranges transmission when the transmitter is at the desire location. Finally, we implement and evaluate the proposed scheme on ZigBee platform with CC2530 radio, and also compare with the real-time reactive scheme in walking scenario. The experimental results show that the M-TPC scheme reduces transmission power by 43.27% and enhances the link reliability by reducing the packet loss rate by 75%.

[1]  Chenguang He,et al.  Toward Ubiquitous Healthcare Services With a Novel Efficient Cloud Platform , 2013, IEEE Transactions on Biomedical Engineering.

[2]  David D. Wentzloff,et al.  Exploiting Channel Periodicity in Body Sensor Networks , 2012, IEEE Journal on Emerging and Selected Topics in Circuits and Systems.

[3]  Muhannad Quwaider,et al.  Body-posture-based dynamic link power control in wearable sensor networks , 2010, IEEE Communications Magazine.

[4]  Ye Li,et al.  Physical Activity Recognition Utilizing the Built-In Kinematic Sensors of a Smartphone , 2013, Int. J. Distributed Sens. Networks.

[5]  Tae-Seong Kim,et al.  A Triaxial Accelerometer-Based Physical-Activity Recognition via Augmented-Signal Features and a Hierarchical Recognizer , 2010, IEEE Transactions on Information Technology in Biomedicine.

[6]  W.G. Scanlon,et al.  A Time-Domain Approach to the Analysis and Modeling of On-Body Propagation Characteristics Using Synchronized Measurements at 2.45 GHz , 2009, IEEE Transactions on Antennas and Propagation.

[7]  Vijay Sivaraman,et al.  Transmission Power Control in Body Area Sensor Networks for Healthcare Monitoring , 2009, IEEE Journal on Selected Areas in Communications.

[8]  Bin Liu,et al.  MAC protocol in wireless body area networks for E-health: challenges and a context-aware design , 2013, IEEE Wireless Communications.

[9]  Kaveh Pahlavan,et al.  Characteristic and Modeling of Human Body Motions for Body Area Network Applications , 2012, Int. J. Wirel. Inf. Networks.

[10]  Ankur Mehta,et al.  Reducing Average Power in Wireless Sensor Networks through Data Rate Adaptation , 2009, 2009 IEEE International Conference on Communications.

[11]  William P. Marnane,et al.  Energy-Efficient Low Duty Cycle MAC Protocol for Wireless Body Area Networks , 2009, IEEE Transactions on Information Technology in Biomedicine.

[12]  Doo Seop Eom,et al.  Link-State-Estimation-Based Transmission Power Control in Wireless Body Area Networks , 2014, IEEE Journal of Biomedical and Health Informatics.

[13]  Chiara Buratti,et al.  A Survey on Wireless Body Area Networks: Technologies and Design Challenges , 2014, IEEE Communications Surveys & Tutorials.