Robust High Data Rate MIMO Underwater Acoustic Communications

Abstract

Our research focuses on multi-input multi-output (MIMO) communications over sparse acoustic channels suffering from frequency modulations. An extension of the recently introduced SLIM algorithm, which stands for sparse learning via iterative minimization, is presented to jointly estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). Moreover, we also consider channel equalization and symbol detection for various MIMO transmission schemes, including both space-time block coding and spatial multiplexing, under the challenging channel conditions. The effectiveness of the proposed approaches is demonstrated using in-water experimental measurements recently acquired during WHOI09 and ACOMM10 experiments. Furthermore we present a semi-blind equalizer implemented by Gibbs sampling techniques, and verify its power using SPACE08 experimental results.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Dec 31, 2010
Accession Number
ADA535636

Entities

People

  • Jiantao Li

Organizations

  • University of Florida

Tags

Communities of Interest

  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Sensors

DTIC Thesaurus Topics

  • Acoustic Channels
  • Acoustic Communications
  • Algorithms
  • Buzzards Bay
  • Channel Estimation
  • Data Rate
  • Detection
  • Doppler Effect
  • Frequency
  • Frequency Modulation
  • Modulation
  • Monte Carlo Method
  • Multiple Input Multiple Output
  • Multiplexing
  • Sampling
  • Transmitters
  • Underwater Acoustic Communications

Fields of Study

  • Engineering

Readers

  • Acoustical Oceanography.
  • Neural Network Machine Learning.
  • Radio communications and signal processing.

Technology Areas

  • Space
  • Space - Space Objects