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

Sensors

Jesús Llor¹ 

[1] Physics and Computer Engineering Department, Miguel Hernandez University, Ave. Universidad S/N, Ed. Alcudia, 03202 Elche, Alicante, Spain; E-Mail

关键词: wireless sensor networks;    underwater acoustic communications;    acoustic propagation;    statistical modeling;    network planning;   

DOI  :  10.3390/s130202279

来源: mdpi

【 摘 要 】

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.).

【 授权许可】

CC BY   
© 2013 by the authors; licensee MDPI, Basel, Switzerland.