Iterative Reception for Acoustic Underwater MIMO Communications

Nordenvaad, Magnus Lundberg; Oberg, T.

doi:10.1109/oceans.2006.307060

Cited by 16 publications

(10 citation statements)

References 8 publications

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“…In Nordenvaad and Oberg (2006), the authors consider the channel as a 1-rate code and use turbo decoding framework to decode the MIMO signals. A widely linear model of the Alamouti code was used for joint equalization and decoding, with a linear equalizer chosen for its low complexity.…”

Section: E Spatial Modulationmentioning

confidence: 99%

Underwater Acoustic Communications and Networking: Recent Advances and Future Challenges

Chitre¹,

Shahabudeen²,

Stojanovic³

2008

mar technol soc j

527

222

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A B S T R A C TThe past 30 years have seen a growing interest in underwater acoustic communications because of its applications in marine research, oceanography, marine commercial operations, the offshore oil industry and defense. Continued research over the years has resulted in improved performance and robustness as compared to the initial communication systems. In this paper, we aim to provide an overview of the key developments in point-to-point communication techniques as well as underwater networking protocols since the beginning of this decade. We also provide an insight into some of the open problems and challenges facing researchers in this field in the near future.protocols for such networks. In this paper, we do not attempt to provide an exhaustive survey of all research in the field, but instead concentrate on ideas and developments that are likely to be the keystone of future underwater communication networks. II. Underwater CommunicationsHigh-speed communication in the underwater acoustic channel has been challenging because of limited bandwidth, extended multipath, refractive properties of the medium, severe fading, rapid time variation and large Doppler shifts. In the initial years, rapid progress was made in deep water communication, but the shallow water channel was considered difficult. In the past decade, significant advances have been made in shallow water communication.

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Section: E Spatial Modulationmentioning

confidence: 99%

Underwater Acoustic Communications and Networking: Recent Advances and Future Challenges

Chitre¹,

Shahabudeen²,

Stojanovic³

2008

mar technol soc j

527

222

View full text Add to dashboard Cite

show abstract

“…4 Limited by the scarce bandwidth, the pursuit of high data rate in UAC leverages the multi-input multi-output (MIMO) scheme (see, e.g., Refs. [7][8][9][10][11][12][13][14][15]. With sufficient diversity, MIMO systems offer enhanced reliability and/or increased data rates compared to their single-input counterparts.…”

Section: Introductionmentioning

confidence: 99%

Multi-input multi-output underwater communications over sparse and frequency modulated acoustic channels

Ling

Zhao

et al. 2011

The Journal of the Acoustical Society of America

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This paper addresses 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 estimate the sparse and frequency modulated acoustic channels. The extended algorithm is referred to as generalization of SLIM (GoSLIM). The sparseness is exploited through a hierarchical Bayesian model, and because GoSLIM is user parameter free, it is easy to use in practical applications. Moreover this paper considers 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.

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“…[4]- [8]. STBC for underwater acoustic channels has been considered for both single-carrier systems [9], and multi-carrier systems [10], [11]. Reference [9] discusses a jointly optimized MIMO-DFE with spacetime trellis codes.…”

Section: Introductionmentioning

confidence: 99%

“…Reference [9] discusses a jointly optimized MIMO-DFE with spacetime trellis codes. In [10], maximum likelihood detection was considered, while [11] considered iterative equalization and decoding.…”

Section: Introductionmentioning

confidence: 99%

Alamouti space time coded OFDM for underwater acoustic channels

Stojanovic

2010

Oceans'10 Ieee Sydney

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Abstract-Alamouti space-time coding is investigated in conjunction with OFDM modulation for high-rate underwater acoustic communications over time varying channels. The scheme's diversity gain is exploited using a low-complexity adaptive multichannel receiver. Performance is demonstrated using experimental data transmitted in a 10 kHz bandwidth over a 1 km shallow water channel south of the Martha's Vineyard island in New England. The two-transmitter Alamouti scheme shows the expected improvement over the same-rate single-transmitter scheme.

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Iterative Reception for Acoustic Underwater MIMO Communications

Cited by 16 publications

References 8 publications

Underwater Acoustic Communications and Networking: Recent Advances and Future Challenges

Underwater Acoustic Communications and Networking: Recent Advances and Future Challenges

Multi-input multi-output underwater communications over sparse and frequency modulated acoustic channels

Alamouti space time coded OFDM for underwater acoustic channels

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