Next Article in Journal
Software Updating in Wireless Sensor Networks: A Survey and Lacunae
Next Article in Special Issue
Sensor Enclosures: Example Application and Implications for Data Coherence
Previous Article in Journal
iMASKO: A Genetic Algorithm Based Optimization Framework for Wireless Sensor Networks
J. Sens. Actuator Netw. 2013, 2(4), 700-716; doi:10.3390/jsan2040700

MIMO Underwater Acoustic Communications in Ports and Shallow Waters at Very High Frequency

1,*  and 2
1 Department of Ocean and Mechanical Engineering, Florida Atlantic University, 101 North Beach Road, Dania Beach, FL 33004, USA 2 ISEN Brest, 20 Cuirassé Bretagne, CS 42807, Brest Cedex 2 29228, France Current address: Laboratoire de Mécanique et d’Acoustique, CNRS UPR 7051, 31 Chemin Joseph Aiguier, Marseille 13402, France. Current address: Thales Underwater Systems SAS, 525 Route des Dolines, BP 157, Sophia-Antipolis Cedex 06903, France.
* Author to whom correspondence should be addressed.
Received: 14 August 2013 / Revised: 23 September 2013 / Accepted: 24 September 2013 / Published: 11 October 2013
(This article belongs to the Special Issue Underwater Sensor Networks)
View Full-Text   |   Download PDF [905 KB, uploaded 11 October 2013]   |   Browse Figures


Hermes is a Single-Input Single-Output (SISO) underwater acoustic modem that achieves very high-bit rate digital communications in ports and shallow waters. Here, the authors study the capability of Hermes to support Multiple-Input-Multiple-Output (MIMO) technology. A least-square channel estimation algorithm is used to evaluate multiple MIMO channel impulse responses at the receiver end. A deconvolution routine is used to separate the messages coming from different sources. This paper covers the performance of both the channel estimation and the MIMO deconvolution processes using either simulated data or field data. The MIMO equalization performance is measured by comparing three relative root mean-squared errors (RMSE), obtained by calculations between the source signal (a pseudo-noise sequence) and the corresponding received MIMO signal at various stages of the deconvolution process; prior to any interference removal, at the output of the Linear Equalization (LE) process and at the output of an interference cancellation process with complete a priori knowledge of the transmitted signal. Using the simulated data, the RMSE using LE is −20.5 dB (where 0 dB corresponds to 100% of relative error) while the lower bound value is −33.4 dB. Using experimental data, the LE performance is −3.3 dB and the lower bound RMSE value is −27 dB.
Keywords: MIMO; underwater; acoustic communications; channel estimation; equalization MIMO; underwater; acoustic communications; channel estimation; equalization
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Share & Cite This Article

Further Mendeley | CiteULike
Export to BibTeX |
EndNote |
MDPI and ACS Style

Real, G.; Beaujean, P.-P.; Bouvet, P.-J. MIMO Underwater Acoustic Communications in Ports and Shallow Waters at Very High Frequency. J. Sens. Actuator Netw. 2013, 2, 700-716.

View more citation formats

Related Articles

Article Metrics


[Return to top]
J. Sens. Actuator Netw. EISSN 2224-2708 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert