Underwater Acoustic Channel Modeling: A Simulation Study

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Underwater Acoustic Channel Modeling: A Simulation Study Powered By Docstoc
					                                                      (IJCSIS) International Journal of Computer Science and Information Security,
                                                      Vol. 10, No. 9, September 2012




               Underwater Acoustic Channel Modeling:
                        A Simulation Study

                     Pallavi Kamal                                                        Taussif Khanna
                Electrical Engineering                                         Institute of Information Technology
              University Teknologi Mara                                     Kohat University of Science and Technology
           40450 Shah Alam, Selangor Darul                                                     Pakistan
                   Ehsan, Malaysia


Abstract—Underwater acoustic (UWA) communications have                or software simulation [1-5]. However, these efforts may
been regarded as one of the most challenging wireless                 not be suitable for those contexts in which a high level
communications due to the unique and complicated properties of        model is required. In other words, how to accurately model
underwater acoustic environments, such as severe multipath            UWA channels for complicated UWA environments is still
delay, large Doppler shift and fast environmental changes.
Therefore, accurate UWA channel modeling is crucial for
                                                                      a challenging issue that has not been well resolved.
achieving high performance UWA communication systems. Since              Bellhop algorithm [6-7] is a beam tracing model for
there is no generalized UWA channel mode, most of existing            predicting acoustic pressure fields in ocean environments.
channel models is either empirical measurement- or simulation-
based channel models. In this paper, we propose a study of            The beam tracing structure leads to a particularly simple
simulation-based UWA channel modeling, which is based on the          algorithm. Bellhop can produce a variety of useful outputs
Bellhop algorithm and Time Variable Acoustic Propagation              including transmission loss, eigenrays, arrivals, and
Model (TVAPM) platform. Our study is capable of handling              received time-series. It allows for range-dependence in the
almost any type of steady and unsteady environmental motion           top and bottom boundaries (altimetry and bathymetry), as
except the modeling of breaking waves.                                well as in the sound speed profile. [8-9] adopted the
    Keywords-underwater acoustic channel modeling; Bellhop            Bellhop algorithm to calculated transmission loss item of
algorithm; VIRTEX platform ; environmental motion                     signal-to-noise ratio (SNR). [10] used Bellhop Gaussian
                                                                      beam tracing program for the acoustic field module. [11]
                     I.    INTRODUCTION                               adopted the Bellhop algorithm to simulate channel impulse
                                                                      response in the presence of effect of wind-generated
   Underwater Acoustic (UWA) communications have
                                                                      bubbles.
been widely used in military and civilian applications for a
long time, such as monitoring of underwater environments,               The Time Variable Acoustic Propagation Model
and unmanned underwater vehicle (UUV) communications.                 (TVAPM) platform [12] aims at generating time variable
However, how to achieve high performance and reliable                 simulated acoustic channel responses between moving
UWA communications is a challenging issue due to the                  sources and receivers in a realistically modeled
complicated underwater environments (e.g., shallow water).            environment. The main objective of this simulator is to
    One of the driving factors in the performance of certain          properly take into account the Doppler effects induced by
UWA communication systems is the Doppler spread, which                source-receiver relative motion as well as the effects of that
is often generated by sea-surface movement. The time-                 motion that propagate through the acoustic channel.
varying nature of the sea surface adds complexity and often
                                                                         In this paper, based on the Bellhop algorithm and the
leads to a statistical description for the variations in the
                                                                      TVAPM platform, we propose a study of UWA channel
received signals. Severe multipath propagation and large
Doppler shift due to source/receiver motion are another two           modeling in complicated underwater environments. The
factors that determine the performance of UWA                         content includes but not limited to the following aspects: (1)
communications. The available bandwidth of the UWA                    source/array initial localization; (2) Doppler shift (in
channel is limited and it highly depends on both                      frequency) estimation; (3) multi-path time delay estimation;
transmission range and frequency. These introduced                    (4) TVAPM platform-based channel modeling with sea-
characteristics restrict the reliable and high performance            surface motion (e.g., wind speed). Our paper will provide a
communications.                                                       useful reference for scientists and engineers who want to
                                                                      simulate any complicated UWA channels for
   Many works have already treated the problem of UWA
                                                                      communications.
channel modeling, either based on empirical measurement



                                                                 25                              http://sites.google.com/site/ijcsis/
                                                                                                 ISSN 1947-5500
                                                       (IJCSIS) International Journal of Computer Science and Information Security,
                                                       Vol. 10, No. 9, September 2012


   The rest of this paper is organized as follows: Section II
is the introduction of the Bellhop algorithm and the
TVAPM platform. Section III is the study of Bellhop
algorithm-based investigation of acoustic signal
propagation and UWA channel properties; Section IV
concludes this paper.
           II.   BELLHOP ALGORITHM AND TVAPM

A. Bellhop Algorithm
 The overall structure of BELLHOP algorithm is shown
in Figure 1. In order to describe the environment and the
geometry of sources and receivers, various files must be
provided. In the most simple and general case, which is
also typical, there is only one such file. It is referred to as
an environmental file (.env) and includes the sound
speed profile, as well as information about the ocean                           Figure 1. Structure of Bellhop algorithm [13]
bottom. However, if there is a range-dependent bottom,
                                                                       B. TVAPM platform
then a bathymetry file (.bty) with range-depth pairs
defining the water depth must be added. Similarly, if                     The TV-APM is a valuable tool to discuss arrival
there is a range dependent ocean sound speed, an SSP                   scattering due to the propagation of wind-driven sea
file with the sound speed tabulated on a regular grid                  surface waves or relative motion between a source
should be shown up. Further, if anyone who wants to                    and an array. Modeling in the future can be oriented
specify an arbitrary bottom reflection coefficient to                  along the following guidelines:
characterize the bottom, then one must provide a bottom                     Accounting for range dependent bottom
reflection coefficient file with angle-reflection
                                                                            properties, shear included.
coefficient pairs defining the reflectivity. Similar
capabilities are implemented for the surface. Thus there
                                                                            Accounting for sound speed fields and sound
is the option of providing a top reflection coefficient and                 speed temporal variability, in particular using
a top shape (.aty file) [13].                                               empirical orthogonal functions.
   Usually one assumes the acoustic source is omni-                         Considering the statistical distribution of travel
directional; however, if there is a source beam pattern,                    times and amplitudes.
then one must provide a source beam pattern file with                       Considering the inclusion of additional acoustic
angle-amplitude pairs defining it. BELLHOP reads these                      models.
files depending on options selected within the main
environmental file. Plot programs (plotssp, plotbty,                                      III.   SIMULATION STUDY
plotbrc, etc.) are provided to display each of the input                 Figures 2-5 provide results of a case study of underwater
files. [13]                                                            acoustic channel properties. Parameter settings for the selected
                                                                       case can be found in Appendix.




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                                                                                                  ISSN 1947-5500
                                                (IJCSIS) International Journal of Computer Science and Information Security,
                                                Vol. 10, No. 9, September 2012


                                                                                              t-tau representation                                         t-f representation
                                                                                      0                                                         0

                                                                                     0.5                                                       0.5




                                                                    time (s)




                                                                                                                              time (s)
                                                                                      1                                                         1

                                                                                     1.5                                                       1.5

                                                                                      2                                                         2
                                                                                       0.68   0.69     0.7    0.71     0.72                          -2000 -1000     0 1000 2000
                                                                                                    delay (s)                                                frequency (Hz)
                                                                                              d-tau representation                                          d-f representation


                                                                                      5                                                         5




                                                                      Doppler (Hz)




                                                                                                                                doppler (Hz)
                                                                                      0                                                         0

                                                                                      -5                                                        -5


                                                                                       0.68   0.69     0.7     0.71    0.72                          -2000 -1000    0 1000 2000
                                                                                                     delay (s)                                               frequency (Hz)



       Figure 2. Result of Static Source                                             Figure 5. Results of simulated channel properties.

                                                                                                                  IV. CONCLUSION
                                                                Bellhop algorithm as well as its associated TVAPM
                                                              platform has been validated to be a powerful to model
                                                              underwater acoustic channels, especially convenient for
                                                              instigating the properties of underwater acoustic channel under
                                                              time-varying conditions. In addition, this channel modeling
                                                              platform can be combined with other underwater acoustic
                                                              communication and network simulation tool (e.g., ns2) to
                                                              evaluate the performance of a whole system.

                                                              Appendix: Parameter settings of the case study

                                                              source_x = [1900 900 5];
                                                              source_v = [0 0 0];
                                                              source_nrays = 2001;
                                                              source_aperture = 60;
         Figure 3. Result of Static Array
                                                              source_ray_step = 10;
                                                              fc = 15000; % frequency (Hz)
                                                              fs_x = 5000; % input baseband signal sampling frequency (Hz)
                                                              bottom_properties = [1465 1.5 0.06];
                                                              %bottom_properties(1) = compressional speed (m/s)
                                                              %bottom_properties(2) = bottom density (g/cm3)
                                                              %bottom_properties(3) = bottom attenuation (dB/wavelength)
                                                               array_x = [2800 400 0];
                                                              array_v = [0 0 0];
                                                              first_hyd = 30;
                                                              last_hyd = 60;
                                                              delta_hyd = 10;
                                                              % Wind induced sea surface wave
                                                              U = 10; % wind speed
                                                              theta = 20; % direction of propagation in degrees
                                                              spreading = 'none';


                                                                                                                      REFERENCES
Figure 4. Result of Source/Array initial positioning
                                                              [1]   A. F. Harris and M. Zorzi, “Modeling the underwater acoustic channel in
                                                                    ns2”, ACM proceedings of the 2nd international confernece on
                                                                    performance evaluation methodologies and tool, pp. 1-8, 2007




                                                         27                                                            http://sites.google.com/site/ijcsis/
                                                                                                                       ISSN 1947-5500
                                                                      (IJCSIS) International Journal of Computer Science and Information Security,
                                                                      Vol. 10, No. 9, September 2012


[2]   S. H. Byun, S. M. Kim, Y. K. Lim and W. Seong, “Time-varying                      [9]    X. Huang and V. B. Lawrence. “Bandwidth-Efficient Bit and Power
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[6]   BELLHOP gaussian beam/finite element beam code [Available]                        [12]   A. J. Silva and O. Rodriguez, “Time-variable avoustic propagation
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