scholarly journals Connectivity on Underwater MI-Assisted Acoustic Cooperative MIMO Networks

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3317
Author(s):  
Qingyan Ren ◽  
Yanjing Sun ◽  
Yu Huo ◽  
Liang Zhang ◽  
Song Li

In traditional underwater wireless sensor networks (UWSNs), it is difficult to establish reliable communication links as the acoustic wave experiences severe multipath effect, channel fading, and ambient noise. Recently, with the assistance of magnetic induction (MI) technique, cooperative multi-input-multi-output (MIMO) is utilized in UWSNs to enable the reliable long range underwater communication. Compared with the acoustic-based UWSNs, the UWSNs adopting MI-assisted acoustic cooperative MIMO are referred to as heterogeneous UWSNs, which are able to significantly improve the effective cover space and network throughput. Due to the complex channel characteristics and the heterogeneous architecture, the connectivity of underwater MI-assisted acoustic cooperative MIMO networks is much more complicated than that of acoustic-based UWSNs. In this paper, a mathematical model is proposed to analyze the connectivity of the networks, which considers the effects of channel characteristics, system parameters, and synchronization errors. The lower and upper bounds of the connectivity probability are also derived, which provide guidelines for the design and deployment of underwater MI-assisted acoustic cooperative MIMO networks. Monte Carlo simulations were performed, and the results validate the accuracy of the proposed model.

2019 ◽  
Vol 21 (1) ◽  
pp. 25-32 ◽  
Author(s):  
Donatella Darsena ◽  
Giacinto Gelli ◽  
Francesco Verde

2019 ◽  
Vol 9 (13) ◽  
pp. 2740
Author(s):  
Akram Ahmed ◽  
Mohamed Younis

To increase underwater acoustic signal detectability and conserve energy, nodes leverage directional transmissions. In addition, nodes operate in a three-dimensional (3D) environment that is categorized as inhomogeneous where a propagating signal changes its direction based on the observed sound speed profile (SSP). Coupling 3D directional transmission with frequent node drifts and the varying underwater SSP complicates the process of selecting suitable transmission angles to maintain underwater communication links. Fundamentally, utilizing directional transmission while nodes are drifting causes breaks in established communication links and thus nodes need to find new angles to reestablish these links. Moreover, selecting arbitrary transmission angles may lead to overlapping beams or result in leaving an underwater region uncovered. To tackle the abovementioned challenges, this paper proposes an autonomous beam selection approach that optimizes underwater communication by selecting non-overlapping beams while mitigating the possibility of missing a region, i.e., maximize coverage. Such optimization is achieved by utilizing a structured angle selection mechanism that accounts for the capability of the used transducer. Moreover, we introduce an algorithm suited for resource constrained nodes to classify rays into different types. Then we divide the underwater medium into regions where each region is identified by the limits of the coverage area of each ray type. Finally, we utilize the limits of these regions to aid nodes in selecting the best ray to reestablish communication with drifted nodes. We validate our contribution through simulation where actual SSPs are leveraged to validate the beam classification process.


2014 ◽  
Vol 21 (5) ◽  
pp. 41-51 ◽  
Author(s):  
Seunghwan Won ◽  
Lajos Hanzo

Frequenz ◽  
2012 ◽  
Vol 66 (7-8) ◽  
Author(s):  
Malgorzata Janson ◽  
Juan Pontes ◽  
Thomas Fügen ◽  
Thomas Zwick

AbstractThis paper presents a computationally effective approach for including dense multipath components in ray tracing simulations of ultra wideband (UWB) channels. Through a combination of a standard ray tracing model with a simple geometric-stochastic model realistic scenario-specific simulations are possible. The frequency and direction selectivity of the channel are reproduced accurately by the model. The structure and parameters of the stochastic part of the model are derived from measurements in the FCC-UWB frequency range. Compared to conventional ray tracing simulations the proposed model reduces considerably the differences between simulated and measured channel characteristics.


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