Chirp FSK based on FRFT for underwater acoustic communication

Zhang, Kaihan; Chen, Ke-Yu; Yuan, Fei; Yi, Jinwang

doi:10.1109/iceiec.2017.8076510

Cited by 8 publications

(2 citation statements)

References 4 publications

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“…The underwater channel is time‐dependent with several pathways, resulting in Inter Symbol Interference (ISI). This unwelcome occurrence of signal distortion interferes with distinct symbols, resulting in a negative effect of frequency spreading and fading, making communication less trustworthy 16 . In this case, modulation plays a crucial role in channels with modest temporal variations by removing the necessity for exceedingly complicated equalizers.…”

Section: Acoustic Communication In Underwatermentioning

confidence: 99%

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Gola

Arya

2023

Concurrency and Computation

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SummaryWireless information routing beneath the ocean, or usually underwater, has supplied the most excellent technical methods of oceanic observations. Traditionally, ocean bottoms have been monitored by placing oceanographic sensors that collect data at specific and defined ocean zones. When the duties are performed, the oceanographic instruments are recovered. Because there is no collaborative exchange of collected data between the collecting point and the monitoring end, data cannot be observed remotely. Underwater sensor networks can be wirelessly connected with sensors and monitors without extensive cable. Underwater wireless sensor networks are what they are called (UWSNs). This article investigates the various aspects of UWSNs, such as their significance, applications, network design, demands, routing, deployments and challenges.

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Section: Acoustic Communication In Underwatermentioning

confidence: 99%

Underwater acoustic sensor networks: Taxonomy on applications, architectures, localization methods, deployment techniques, routing techniques, and threats: A systematic review

Gola

Arya

2023

Concurrency and Computation

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“…If the different signals have different frequency slopes, the signals will have peaks at different positions with different transform orders on the FrFT spectrum. In this way, the correct transform order with peaks in each FrFT spectrum is called the optimal transform order, which is denoted by αopt [27,30]. The FrFT equation is Faf(u)=∫Kα(u,x)f(x)dx, where the term Kα(u,x) is expressed as Kα(u,x)={Aαexp{iπ[cot(α)(x2+u2)−2csc(α)ux]}, (α≠nπ)δ(u−x) (α=2nπ)δ(u+x) (α=(2n±1)π)…”

Section: Receiver Design Based On Fractional Fourier Transformmentioning

confidence: 99%

Chirp-Based FHSS Receiver with Recursive Symbol Synchronization for Underwater Acoustic Communication

Lee

Park

Kang

et al. 2018

Sensors

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In this paper, we propose a covert underwater acoustic communication method that is robust to fading using a chirp signal combined with a frequency-hopping spread spectrum scheme. A fractional Fourier transform, which estimates the slope of the signal frequency variation, is applied to the receiver to enable a robust and reliable symbol estimation with respect to the frequency and irregular phase variations. In addition, since the recursive symbol synchronization can be implemented using a chirp signal, compression and expansion effects due to the Doppler shift can be mitigated. Simulation and lake trials were performed to verify the performance of the proposed method. The simulation was performed by two different methods.

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