Performance of a space‐time trellis‐coded multiple‐input, multiple‐output (MIMO) underwater acoustic communication system for the littoral

2005 ◽  
Vol 118 (3) ◽  
pp. 2038-2038
Author(s):  
Richard F. Ormondroyd ◽  
Jasdeep S. Dhanoa
2016 ◽  
Vol 140 (4) ◽  
pp. 3230-3230
Author(s):  
Takuya Shimura ◽  
Yukihiro Kida ◽  
Mitsuyasu Deguchi ◽  
Kohji Meguro ◽  
Yoshitaka Watanabe ◽  
...  

2015 ◽  
Vol 49 (6) ◽  
pp. 161-165 ◽  
Author(s):  
Pierre-Philippe J. Beaujean

AbstractAs underwater acoustic communication technology is becoming more mature, it is increasingly used in the marine industry, scientific community, and military. This article enquires about the latest developments produced by academia and identifies new technological trends in this field. The latest trends in point-to-point communications, multiple-input multiple-output technology, and underwater acoustic networking are reviewed.


2020 ◽  
Vol 16 (12) ◽  
pp. 155014772097989
Author(s):  
Gaoli Zhao ◽  
Jianping Wang ◽  
Junping Song ◽  
Wei Chen

Multiple-input multiple-output is a commonly used technology supporting for high-rate transmission over frequency-selective fading channels with multiple antennas. Vertical-Bell Laboratories Layered Space-Time is a detection method of a multiple-input multiple-output system, which establishes a direct correspondence between antennas and layers. Studies demonstrate that multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time is a meaningful way for underwater acoustic networks of high performance. However, considering the hardware constraints and energy consumption, achieving a trade-off between the bit error ratio and complexity is a crucial issue for underwater acoustic networks of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time systems. This article proposes a novel signal detection algorithm of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time. First, we address the unitary matrix of the underwater acoustic channel by LDLH decomposition. Second, we order the detection sequence based on the permutation matrix. Third, we detail the implementation of interference cancelation and slice processing. Finally, we perform experiments for comparing the bit error ratio, energy consumption, processing delay, and complexity of the proposed algorithm with zero-forcing Vertical-Bell Laboratories Layered Space-Time, minimum mean square error Vertical-Bell Laboratories Layered Space-Time, and maximum likelihood Vertical-Bell Laboratories Layered Space-Time. Results indicate that our algorithm maintains bit error ratio and the processing delay to that of maximum likelihood Vertical-Bell Laboratories Layered Space-Time algorithm. However, it reduces the energy consumption, which achieves a good trade-off between performance and complexity. This work supports on constructing underwater acoustic networks of multiple-input multiple-output Vertical-Bell Laboratories Layered Space-Time system.


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