TY - JOUR
T1 - Dynamic Magnetic Induction Wireless Communications for Autonomous-Underwater-Vehicle-Assisted Underwater IoT
AU - Wei, Debing
AU - Yan, Li
AU - Huang, Chenpei
AU - Wang, Jie
AU - Chen, Jiefu
AU - Pan, Miao
AU - Fang, Yuguang
PY - 2020/10
Y1 - 2020/10
N2 - Leveraging the mobility of autonomous underwater vehicles (AUVs) to collect and deliver data among different underwater devices enables numerous underwater Internet-of-Things (UW-IoT) applications. However, the most versatile underwater acoustic communications (UACs) may not be suitable in the AUV-assisted UW-IoT scenarios, considering the high cost and high power consumption of acoustic transducers, as well as high error rates of UACs due to the complex underwater acoustic channel conditions. Alternatively, we propose to apply the low-power magnetic induction (MI)-based wireless communications for AUV data dissemination and collection. Due to the mobility of AUVs and the underwater turbulence, MI channels between AUVs and other underwater devices are no longer stable and static, which poses great challenges to establish reliable MI links. To tackle this problem, we investigate the dynamic MI wireless communications in this article. We first mathematically characterize the dynamic MI channel when an AUV approaches its target for data collection. Based on this dynamic channel model, the dynamic communication range and available bandwidth of MI are derived. We also build an MI wireless communication system that can work within a dynamic range. The communication performances are evaluated through numerical simulations as well as underwater experiments.
AB - Leveraging the mobility of autonomous underwater vehicles (AUVs) to collect and deliver data among different underwater devices enables numerous underwater Internet-of-Things (UW-IoT) applications. However, the most versatile underwater acoustic communications (UACs) may not be suitable in the AUV-assisted UW-IoT scenarios, considering the high cost and high power consumption of acoustic transducers, as well as high error rates of UACs due to the complex underwater acoustic channel conditions. Alternatively, we propose to apply the low-power magnetic induction (MI)-based wireless communications for AUV data dissemination and collection. Due to the mobility of AUVs and the underwater turbulence, MI channels between AUVs and other underwater devices are no longer stable and static, which poses great challenges to establish reliable MI links. To tackle this problem, we investigate the dynamic MI wireless communications in this article. We first mathematically characterize the dynamic MI channel when an AUV approaches its target for data collection. Based on this dynamic channel model, the dynamic communication range and available bandwidth of MI are derived. We also build an MI wireless communication system that can work within a dynamic range. The communication performances are evaluated through numerical simulations as well as underwater experiments.
KW - Autonomous underwater vehicular (AUV)
KW - channel modeling
KW - magnetic induction (MI)
KW - underwater wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85092728855&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85092728855&origin=recordpage
U2 - 10.1109/JIOT.2020.2997709
DO - 10.1109/JIOT.2020.2997709
M3 - RGC 21 - Publication in refereed journal
SN - 2327-4662
VL - 7
SP - 9834
EP - 9845
JO - IEEE Internet of Things Journal
JF - IEEE Internet of Things Journal
IS - 10
M1 - 9099791
ER -