Computer Science ›› 2019, Vol. 46 ›› Issue (9): 113-119.doi: 10.11896/j.issn.1002-137X.2019.09.015

• Network & Communication • Previous Articles     Next Articles

Acoustic Signal Propagation Model and Its Performance in Cave Environment

HE Ming-xing1, ZHOU Jie1,2, WU Peng1, LIU Yang1   

  1. (Deparment of Communications,Nanjing University of Information Science and Technology,Nanjing 210044,China)1;
    (Deparment of Electronic and Electrical Engineering,Niigata University,Niigata 950-2181,Japan)2
  • Received:2018-08-06 Online:2019-09-15 Published:2019-09-02

Abstract: In view of the cave environment,this paper presented a geometric model based on the new environment in the cave.The channel on both sides of the cave gradually widen (narrow) from the entrance to the depth.According to the geometric model,and by means of ray theory,this paper assumed that both sides of the channel surface are approximate smooth,and proposed a random channel model of single transmission and single reception for acoustic signal communication system in cave environment.According to the geometric model,the influence of channel opening angle on channel distribution,instant channel capacity,time autocorrelation function,frequency correlation function,Doppler power spectral density and power delay distribution is studied.The theoretical and simulation results show that compared with the case where both sides of the channel are parallel (i.e.the opening angle of both sides is 0),the statistical characteristics of the acoustic channel wireless communication system will be significantly affected by only a small change in the ope-ning angle of both sides of the channel,and the parallel is a special case of this research content.

Key words: Acoustic signal stochastic model, Channel envelope distribution, Doppler power spectral density, Power delay distribution, Frequency correlation function

CLC Number: 

  • TN911.6
[1]RANJAN A,SAHU H,MISRA P.Wave Propagation Model for Wireless Communication in Underground Mines[C]//Bombay Section Symposium.IEEE,2016.
[2]CHITRE,MANDAR.A high-frequency warm shallow wateracoustic communications channel model and measurements[J].The Journal of the Acoustical Society of America,2007,122(5):2580-2586.
[3]SUN Z,AKYILDIZ.Channel modeling and analysis for wireless networks in underground mines and road tunnels[J].IEEE Transactions on Communications,2010,58(6):1758-1768.
[4]ZAJI′C A G.Statistical modeling of MIMO mobile-to-mobile underwater channels[J].IEEE Transactions on Vehicular Technology.Veh.Technol,2011,60(4):1337-1351.
[5]QARABAQI P,STOJANOVIC M,et al.Statistical Characterization and Computationally Efficient Modeling of a Class of Underwater Acoustic Communication Channels[J].IEEE Journal of Oceanic Engineering,2013,38(4):701-717.
[6]NADERI M,PATZOLD M,ZAJIC A G.A geometry-basedchannel model for shallow underwater acoustic channels under rough surface and bottom scattering conditions[C]//2014 IEEE Fifth International Conference on Communications and Electronics (ICCE).IEEE,2014.
[7]QARABAQI P,STOJANOVIC M.Statistical modeling of ashallow water acoustic communication channel[C]//International Conference on Underwater Acoust.IEEE,2009.
[8]ABDI A,GUO H.Signal Correlation Modeling in Acoustic Vector Sensor Arrays[J].IEEE Transactions on Signal Processing,2009,57(3):892-903.
[9]ZAAROUR N,KANDIL N,HAKEM N.An accurate neuralnetwork approach in modeling an UWB channel in an underground mine[C]//IEEE Antennas & Propagation Society International Symposium.IEEE,2013.
[10]BOUVET P,LOUSSERT A.Capacity analysis of underwater acoustic MIMO communications[C]//Oceans.IEEE,2010.
[11]BIN L,XUE-LI Z,HUI-GUO Z,et al.Modeling and Performance Simulation for Wireless Transmission Channels in the Confined Space[C]//Information Technology & Artificial Intelligence Conference.IEEE,2014.
[12]MABROUK I B,TALBI L,NEDIL M.Performance Evaluation of a MIMO System in Underground Mine Gallery[J].IEEE Antennas & Wireless Propagation Letters,2012,11(4):830-833.
[13]KHAN A R,GULHANE S M,KAUSHIK P G.PerformanceComparison of Ultra Wide Band IEEE Channel and Underground Mine Channel[C]//International Conference on Wireless Communications.IEEE,2012.
[14]JENSEN F B,KUPERMAN W A,PORTER M B,et al.Computational Ocean Acoustics(2nd ed) .New York,NY,USA: Springer,2011.
[15]PÄTZOLD M,TALHA.On the statistical properties of sum-ofcisoids-based mobile radio channel models//The Tenth International Symposium on Wireless Personal Multimedia Communications (WPMC).IEEE,2007.
[16]TELATAR E.Capacity of Multi-antenna Gaussian Channels[J].European Transactions on Telecommunications,1999,10(6):585-595.
[17]STOJANOVIC M.On the relationship between capacity and distance in an underwater acoustic communication channel[J].ACM SIGMOBILE Mobile Computing and Communications Review,2007,11(4):34.
[18]PROAKIS J.Probability,random variables and stochasticprocesses[J].IEEE Transactions on Acoustics,Speech,and Signal Processing,2003,33(6):1637-1637.
[19]HOGSTAD B O,GUTIÉRREZ C A.Classes of sum-of-cisoidsprocesses and their statistics for the modeling and simulation of mobile fading channels[J].EURASIP Journal on Wireless Communications and Networking,2013,2013(1):125.
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