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Open AccessArticle

Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks

Physics and Computer Engineering Department, Miguel Hernandez University, Ave. Universidad S/N, Ed. Alcudia, 03202 Elche, Alicante, Spain
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Sensors 2013, 13(2), 2279-2294; https://doi.org/10.3390/s130202279
Received: 28 December 2012 / Revised: 6 February 2013 / Accepted: 7 February 2013 / Published: 8 February 2013
(This article belongs to the Special Issue Last Trends in Acoustic Sensing)
In an underwater acoustic channel, the propagation conditions are known to vary in time, causing the deviation of the received signal strength from the nominal value predicted by a deterministic propagation model. To facilitate a large-scale system design in such conditions (e.g., power allocation), we have developed a statistical propagation model in which the transmission loss is treated as a random variable. By applying repetitive computation to the acoustic field, using ray tracing for a set of varying environmental conditions (surface height, wave activity, small node displacements around nominal locations, etc.), an ensemble of transmission losses is compiled and later used to infer the statistical model parameters. A reasonable agreement is found with log-normal distribution, whose mean obeys a log-distance increases, and whose variance appears to be constant for a certain range of inter-node distances in a given deployment location. The statistical model is deemed useful for higher-level system planning, where simulation is needed to assess the performance of candidate network protocols under various resource allocation policies, i.e., to determine the transmit power and bandwidth allocation necessary to achieve a desired level of performance (connectivity, throughput, reliability, etc.). View Full-Text
Keywords: wireless sensor networks; underwater acoustic communications; acoustic propagation; statistical modeling; network planning wireless sensor networks; underwater acoustic communications; acoustic propagation; statistical modeling; network planning
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MDPI and ACS Style

Llor, J.; Malumbres, M.P. Statistical Modeling of Large-Scale Signal Path Loss in Underwater Acoustic Networks. Sensors 2013, 13, 2279-2294.

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