Throughput Improvement in Backscatter-based Wireless Body Area Network

We consider a wireless body sensor network (WBAN) which utilizes backscatter technology for transmission between sensor nodes and the gateway. Backscatter is a passive communication technology which enables a self-sustainable communication operation, thus it is effective and desired in energy constrained network such as WBAN. In this backscatter-based WBAN, gateway not only receives the sensor data but also has a role of power source continuously emitting RF carrier signal to stimulate the transmissions. As the backscatter communication can work in a battery-less fashion, the first priority design target is to improve the network throughput. Toward this, emitting power and transmission time are jointly optimized by leveraging the periodic fluctuation of WBAN channel. The idea of this work is based on that fact that the temporal fluctuation of WBAN channel caused by walking movements can be predicted, and the throughput improvement can be thus formulated as a convex optimization problem which derives a highly effective resources allocation strategy. Our experimental results show that the proposed solution can significantly improve the throughput performance.

[1]  Björn Eskofier,et al.  Stride Segmentation during Free Walk Movements Using Multi-Dimensional Subsequence Dynamic Time Warping on Inertial Sensor Data , 2015, Sensors.

[2]  Bin Liu,et al.  Medium Access Control for Wireless Body Area Networks with QoS Provisioning and Energy Efficient Design , 2017, IEEE Transactions on Mobile Computing.

[3]  Bin Liu,et al.  Joint Power-Rate-Slot Resource Allocation in Energy Harvesting-Powered Wireless Body Area Networks , 2018, IEEE Transactions on Vehicular Technology.

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

[5]  Mohammad Rostami,et al.  Enabling Practical Backscatter Communication for On-body Sensors , 2016, SIGCOMM.

[6]  José Mendes,et al.  Survey and Taxonomy of Transmissions Power Control Mechanisms for Wireless Body Area Networks , 2018, IEEE Communications Surveys & Tutorials.

[7]  M. S. Reynolds,et al.  Battery-free multichannel digital ECG biotelemetry using UHF RFID techniques , 2013, 2013 IEEE International Conference on RFID (RFID).

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

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

[10]  Guang-Zhong Yang,et al.  Toward Pervasive Gait Analysis With Wearable Sensors: A Systematic Review , 2016, IEEE Journal of Biomedical and Health Informatics.

[11]  Zhu Han,et al.  Wireless Powered Communication Networks: Research Directions and Technological Approaches , 2017, IEEE Wireless Communications.

[12]  Joshua R. Smith,et al.  FM Backscatter: Enabling Connected Cities and Smart Fabrics , 2017, NSDI.

[13]  Ye Li,et al.  Gait-Cycle-Driven Transmission Power Control Scheme for a Wireless Body Area Network , 2018, IEEE Journal of Biomedical and Health Informatics.

[14]  Colby Boyer,et al.  — Invited Paper — Backscatter Communication and RFID: Coding, Energy, and MIMO Analysis , 2014, IEEE Transactions on Communications.

[15]  Qian Zhang,et al.  Battery-free sensing platform for wearable devices: The synergy between two feet , 2016, IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications.

[16]  David Victor Thiel,et al.  Self-Calibrating Body Sensor Network Based on Periodic Human Movements , 2015, IEEE Sensors Journal.

[17]  Reza Abrishambaf,et al.  A Low Traffic Overhead Transmission Power Control for Wireless Body Area Networks , 2018, IEEE Sensors Journal.