Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data
The underwater acoustic channel is remarkably dependent on the considered scenario and the environmental conditions. In fact, channel impairments differ significantly in shallow water with respect to deep water, and the presence of external factors such as snapping shrimps, bubbles, rain, or ships p...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-07-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/11/14/2262 |
| _version_ | 1797439762122932224 |
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| author | Filippo Campagnaro Nicola Toffolo Michele Zorzi |
| author_facet | Filippo Campagnaro Nicola Toffolo Michele Zorzi |
| author_sort | Filippo Campagnaro |
| collection | DOAJ |
| description | The underwater acoustic channel is remarkably dependent on the considered scenario and the environmental conditions. In fact, channel impairments differ significantly in shallow water with respect to deep water, and the presence of external factors such as snapping shrimps, bubbles, rain, or ships passing nearby, changes of temperature, and wind strength can change drastically the link quality in different seasons and even during the same day. Legacy mathematical models that consider these factors exist, but are either not very accurate, like the Urick model, or very computationally demanding, like the Bellhop ray tracer. Deterministic models based on lookup tables (LUTs) of sea trial measurements are widely used by the research community to simulate the acoustic channel in order to verify the functionalities of a network in certain water conditions before the actual deployment. These LUTs can characterize the link quality by observing, for instance, the average packet error rate or even a time varying packet error rate computed within a certain time window. While this procedure characterizes well the acoustic channel, the obtained simulation results are limited to a single channel realization, making it hard to fully evaluate the acoustic network in different conditions. In this paper, we discuss the development of a statistical channel model based on the analysis of real field experiment data, and compare its performance with the other channel models available in the DESERT Underwater network simulator. |
| first_indexed | 2024-03-09T11:58:43Z |
| format | Article |
| id | doaj.art-941956db203e4f31a5c374f4121b5af7 |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-09T11:58:43Z |
| publishDate | 2022-07-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-941956db203e4f31a5c374f4121b5af72023-11-30T23:06:28ZengMDPI AGElectronics2079-92922022-07-011114226210.3390/electronics11142262Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment DataFilippo Campagnaro0Nicola Toffolo1Michele Zorzi2Department of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, ItalyDepartment of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, ItalyDepartment of Information Engineering, University of Padova, Via Gradenigo 6b, 35131 Padova, ItalyThe underwater acoustic channel is remarkably dependent on the considered scenario and the environmental conditions. In fact, channel impairments differ significantly in shallow water with respect to deep water, and the presence of external factors such as snapping shrimps, bubbles, rain, or ships passing nearby, changes of temperature, and wind strength can change drastically the link quality in different seasons and even during the same day. Legacy mathematical models that consider these factors exist, but are either not very accurate, like the Urick model, or very computationally demanding, like the Bellhop ray tracer. Deterministic models based on lookup tables (LUTs) of sea trial measurements are widely used by the research community to simulate the acoustic channel in order to verify the functionalities of a network in certain water conditions before the actual deployment. These LUTs can characterize the link quality by observing, for instance, the average packet error rate or even a time varying packet error rate computed within a certain time window. While this procedure characterizes well the acoustic channel, the obtained simulation results are limited to a single channel realization, making it hard to fully evaluate the acoustic network in different conditions. In this paper, we discuss the development of a statistical channel model based on the analysis of real field experiment data, and compare its performance with the other channel models available in the DESERT Underwater network simulator.https://www.mdpi.com/2079-9292/11/14/2262underwater acoustic channelhidden Markov modelDESERT Underwater network simulations |
| spellingShingle | Filippo Campagnaro Nicola Toffolo Michele Zorzi Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data Electronics underwater acoustic channel hidden Markov model DESERT Underwater network simulations |
| title | Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data |
| title_full | Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data |
| title_fullStr | Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data |
| title_full_unstemmed | Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data |
| title_short | Modeling Acoustic Channel Variability in Underwater Network Simulators from Real Field Experiment Data |
| title_sort | modeling acoustic channel variability in underwater network simulators from real field experiment data |
| topic | underwater acoustic channel hidden Markov model DESERT Underwater network simulations |
| url | https://www.mdpi.com/2079-9292/11/14/2262 |
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