Wireless Body Area Networks Node Sleep Strategy Based On Compressed Sensing and Sparse Representation

DOI

10.2991/icadme-16.2016.156How to use a DOI?

Keywords

WBAN; sleep strategy; compressed sensing; sparse representation

Abstract

Aiming to the problem that the battery energy of the node is limited and not easy to be replaced in WBAN, this paper proposes a new node sleep strategy based on compressed sensing and sparse representation theory (NSS-CS), which using the compressed sensing theory to compress the test samples, and adopting the sparse representation theory to recognize them. When the physiological signals collected by the nodes are in the normal range, NSS-CS can identify those normal signals, stop nodes to transmit normal signals, and make nodes convert into a sleep state to prolong the sleep time of nodes and reduce the amount of transmitting data, thus the node energy consumption can be reduced. Using NS2 software, the simulation of node delay and energy consumption have been implemented, the simulation results show that, WBAN physiological signals are usually in a stable range, compared with the traditional TDMA and BCMAC protocols, the NSS-CS can effectively reduce the energy consumption and delay.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Jiashun Chen
AU  - Yuebin Zhou
AU  - Tao Wang
PY  - 2017/07
DA  - 2017/07
TI  - Wireless Body Area Networks Node Sleep Strategy Based On Compressed Sensing and Sparse Representation
BT  - Proceedings of the 2016 6th International Conference on Advanced Design and Manufacturing Engineering (ICADME 2017)
PB  - Atlantis Press
SP  - 876
EP  - 883
SN  - 2352-5401
UR  - https://doi.org/10.2991/icadme-16.2016.156
DO  - 10.2991/icadme-16.2016.156
ID  - Chen2017/07
ER  -