An Efficient Cross-Layer Reliable Retransmission Scheme for the Human Body Shadowing in IEEE 802.15.6-Based Wireless Body Area Networks

In recent years, a number of middle-aged and elderly people with chronic diseases are increasing. In addition, patients with chronic diseases do not cause health harm in a short period and need long-term hospitalization. Thus, wireless body area network is the best scheme for daily care. According to the human physiological information, it not only sends real-time notifications to users but also reduces delays of the notification regarding patients’ conditions. The physician early identifies the cause of disease and applies remedies according to indications. Daily activities of a person affect the transmission signal of sensor nodes such as walk or run. Thus, the sensor nodes, which have to retransmit the failed frames, are continuously interfered a period time by human body shadowing, so the retransmission procedure should be deferred. If the sensor nodes immediately retransmit the failed frames, they may suffer from the human posture interference again. Therefore, we propose an efficient cross-layer reliable retransmission scheme (CL-RRS) in IEEE 802.15.6 without additional control overheads. The proposed scheme not only detects the information of the sensor nodes with failed transmission frames to allocate retransmission resources, but also increases the successful probability of frame retransmission. Simulation results validated by our mathematical analysis show that the CL-RRS significantly improves frame loss rate and average transmission time, as well as reduces power consumption.

[1]  Jelena V. Misic,et al.  Performance analysis of IEEE 802.15.6 under saturation condition and error-prone channel , 2011, 2011 IEEE Wireless Communications and Networking Conference.

[2]  David W. Smith,et al.  Cooperative receive diversity for coded GFSK body-area communications , 2011 .

[3]  Judith E. Terrill,et al.  Channel Models for Medical Implant Communication , 2010, Int. J. Wirel. Inf. Networks.

[4]  Mehmet Rasit Yuce,et al.  Wireless Body Area Network (WBAN) for Medical Applications , 2010 .

[5]  Jim Morrison,et al.  An energy analysis of IEEE 802.15.6 scheduled access modes , 2010, 2010 IEEE Globecom Workshops.

[6]  Rui Pan,et al.  An Opportunistic Relay Protocol With Dynamic Scheduling in Wireless Body Area Sensor Network , 2015, IEEE Sensors Journal.

[7]  Tharaka A. Lamahewa,et al.  Propagation Models for Body-Area Networks: A Survey and New Outlook , 2013, IEEE Antennas and Propagation Magazine.

[8]  Ian F. Akyildiz,et al.  Wireless sensor networks: a survey , 2002, Comput. Networks.

[9]  Abbas Jamalipour,et al.  Wireless Body Area Networks: A Survey , 2014, IEEE Communications Surveys & Tutorials.

[10]  Monica Nicoli,et al.  Physical Modeling and Performance Bounds for Device-free Localization Systems , 2015, IEEE Signal Processing Letters.

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

[12]  David B. Smith,et al.  Challenges in body area networks for healthcare: the MAC , 2012, IEEE Communications Magazine.

[13]  Ingrid Moerman,et al.  A survey on wireless body area networks , 2011, Wirel. Networks.

[14]  D. Goswami,et al.  Experimental determination of path loss and delay dispersion parameters for on-body UWB WBAN channel , 2015, 2015 IEEE International Conference on Signal Processing, Informatics, Communication and Energy Systems (SPICES).

[15]  Chin-Fu Kuo,et al.  An Adaptive Contention Control Strategy for IEEE 802.15.4-Based Wireless Sensor Networks , 2009, IEEE Transactions on Vehicular Technology.