Channel estimation model for underwater Acoustic Sensor Network

Chavhan, Jyotsna W.; Sarate, G. G.

doi:10.1109/iic.2015.7150887

Cited by 4 publications

(2 citation statements)

References 7 publications

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“…Multi-path propagation and Doppler effects are recognized as one of the most challenging factors of the underwater acoustic channel [27], [28], [29]. The more common techniques to approximately simulate the underwater acoustic channel vary from signalto-noise ratio (SNR)-based channel models that rely on empirical equations as seen in [8] to models that are based on the assumption of Rayleigh signal fading in [30], [31].…”

Section: B Underwater Channelmentioning

confidence: 99%

Underwater Acoustic Communication Receiver Using Deep Belief Network

Lee-Leon¹,

Yuen²,

Herremans³

2021

Preprint

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Underwater environments create a challenging channel for communications. In this paper, we design a novel receiver system by exploring the machine learning technique-Deep Belief Network (DBN)-to combat the signal distortion caused by the Doppler effect and multi-path propagation. We evaluate the performance of the proposed receiver system in both simulation experiments and sea trials. Our proposed receiver system comprises of DBN based de-noising and classification of the received signal. First, the received signal is segmented into frames before the each of these frames is individually pre-processed using a novel pixelization algorithm. Then, using the DBN based de-noising algorithm, features are extracted from these frames and used to reconstruct the received signal. Finally, DBN based classification of the reconstructed signal occurs. Our proposed DBN based receiver system does show better performance in channels influenced by the Doppler effect and multi-path propagation with a performance improvement of 13.2dB at 10 −3 Bit Error Rate (BER).

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Section: B Underwater Channelmentioning

confidence: 99%

Underwater Acoustic Communication Receiver Using Deep Belief Network

Lee-Leon¹,

Yuen²,

Herremans³

2021

Preprint

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“…[4][5][6] In general, the time delay and Doppler frequency shift joint estimation can be achieved by means of resampling and timedomain correlation, 7 which can be only applied to same Doppler frequency shift for multi-path. With the development of underwater acoustic sensor networks, multi-user simultaneous communication is also essential 8,9 and some multiple-access technologies are also proposed for distinguishing multi-user.…”

Section: Introductionmentioning

confidence: 99%

A fractional Fourier transform–based channel estimation algorithm in single-carrier direct sequence code division multiple access underwater acoustic communication system

Zhou

Zhao

Chi

et al. 2019

International Journal of Distributed Sensor Networks

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Due to the complexity and variability of the underwater acoustic channel, the communication signal is affected by multipath, time delay, and Doppler frequency shift. Based on the advantageous characteristics of fractional Fourier transform on chirp signal processing, a fractional Fourier transform-based algorithm using combined linear frequency-modulated signal is proposed, which can estimate parameters of underwater acoustic channel and has a better performance than the existing methods. To distinguish multiuser in underwater acoustic communication system, a single-carrier direct sequence code division multiple access communication system combined with the fractional Fourier transform-based algorithm is proposed. Thus, a preliminary study on underwater multi-target identification is carried out. The simulation and experimental results show that the fractional Fourier transform-based algorithm is simple and effective, and the energy can be focused at the ''best'' fractional order, which can directly determine the multi-path number and complete the channel estimation. The proposed single-carrier direct sequence code division multiple access communication system has good performance on bit error rate when we use corresponding spreading code to distinguish multiuser .

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