Spatially correlated underwater acoustic multiple-input and multiple-output channel model and its application to estimation of channel capacity

Joonsuk Kim, Il Suek Koh, Yongshik Lee

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In this paper, we present a multiple-input and multiple-output (MIMO) channel signal model for underwater acoustic communication systems. This model uses the ray-tracing method to obtain the deterministic part of a channel signal, whereas the fluctuating part is obtained on the basis of the scattering coefficient of the time-varying ocean surface. For the accurate estimation of the channel capacity, spatial correlation is considered during channel signal generation. The validity of the proposed model is verified by comparing it with known ideal solutions. Moreover, results obtained from experimental data are provided to support the proposed model. MIMO channel signals generated by the model can be used to estimate the channel capacity in various communication scenarios.

Original languageEnglish
Article number07HG01
JournalJapanese Journal of Applied Physics
Volume54
Issue number7
DOIs
Publication statusPublished - 2015 Jul 1

Fingerprint

channel capacity
Underwater acoustics
underwater acoustics
Channel capacity
output
ocean surface
scattering coefficients
Ray tracing
ray tracing
telecommunication
Communication systems
communication
Scattering
Communication
estimates

All Science Journal Classification (ASJC) codes

  • Engineering(all)
  • Physics and Astronomy(all)

Cite this

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AB - In this paper, we present a multiple-input and multiple-output (MIMO) channel signal model for underwater acoustic communication systems. This model uses the ray-tracing method to obtain the deterministic part of a channel signal, whereas the fluctuating part is obtained on the basis of the scattering coefficient of the time-varying ocean surface. For the accurate estimation of the channel capacity, spatial correlation is considered during channel signal generation. The validity of the proposed model is verified by comparing it with known ideal solutions. Moreover, results obtained from experimental data are provided to support the proposed model. MIMO channel signals generated by the model can be used to estimate the channel capacity in various communication scenarios.

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