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Gotowe bibliografie tematyczne / Doubly spread channels

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Artykuły w czasopismach

Gotowa bibliografia na temat „Doubly spread channels”

Autor: Grafiati

Data publikacji: 6 września 2023

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Artykuły w czasopismach na temat "Doubly spread channels"

1

Zeng, Wen-Jun, and Xue Jiang. "Time reversal communication over doubly spread channels." Journal of the Acoustical Society of America 132, no. 5 (2012): 3200–3212. http://dx.doi.org/10.1121/1.4754524.

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2

Eggen, Trym H., and James C. Preisig. "Underwater acoustic communication over doubly spread channels." Journal of the Acoustical Society of America 101, no. 5 (1997): 3157. http://dx.doi.org/10.1121/1.419090.

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3

Zeng, Wen-Jun, and Xue Jiang. "Time reversal communication over doubly spread channels." Journal of the Acoustical Society of America 134, no. 5 (2013): 4033. http://dx.doi.org/10.1121/1.4830726.

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4

Zhang, Yang, Qunfei Zhang, Chengbing He, and Chao Long. "Channel estimation for OTFS system over doubly spread sparse acoustic channels." China Communications 20, no. 1 (2023): 50–65. http://dx.doi.org/10.23919/jcc.2023.01.005.

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5

Zeng, Wen-Jun, and Wen Xu. "Fast estimation of sparse doubly spread acoustic channels." Journal of the Acoustical Society of America 131, no. 1 (2012): 303–17. http://dx.doi.org/10.1121/1.3665992.

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6

Drumheller, David Mark, and Dennis W. Ricker. "Receiver-transmitter optimization for detection in doubly spread channels." Journal of the Acoustical Society of America 89, no. 4 (1991): 1714–23. http://dx.doi.org/10.1121/1.401005.

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7

Li, Jie, Fangjiong Chen, Songzuo Liu, Hua Yu, and Fei Ji. "Estimation of Overspread Underwater Acoustic Channel Based on Low-Rank Matrix Recovery." Sensors 19, no. 22 (2019): 4976. http://dx.doi.org/10.3390/s19224976.

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Streszczenie:

In this paper, the estimation of overspread, i.e., doubly spread underwater acoustic (UWA) channels of strong dispersion is considered. We show that although the UWA channel dispersion causes the degeneration of channel sparsity, it leads to a low-rank structure especially when the channel delay-Doppler-spread function is separable in delay and Doppler domain. Therefore, we introduce the low-rank criterion to estimate the UWA channels, which can help to improve the estimation performance in the case of strong dispersion. The estimator is based on the discrete delay-Doppler-spread function representation of channel, and is formulated as a low-rank matrix recovery problem which can be solved by the singular value projection technique. Simulation examples are carried out to demonstrate the effectiveness of the proposed low-rank-based channel estimator.

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8

McDonald, Vincent K., Richard C. Shockley, Joseph A. Rice, and Dale Green. "Probe signals for obtaining impulse response of doubly‐spread channels." Journal of the Acoustical Society of America 102, no. 5 (1997): 3118. http://dx.doi.org/10.1121/1.420575.

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9

Bhadouria, Vijay Singh, Monika Agrawal, and Ritesh Kumar. "An unsupervised clustering-based scale-lag receiver design approach for the doubly selective underwater acoustic channel." Journal of the Acoustical Society of America 152, no. 1 (2022): 342–53. http://dx.doi.org/10.1121/10.0012349.

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Streszczenie:

This paper details the architecture of a novel scale-lag rake receiver for the doubly selective underwater acoustic (UWA) channel. The shallow UWA channel is known to have a large Doppler spread. The cause of this is primarily due to the large spread of the angle of arrival of the received signal's paths. The Doppler scale value is dependent on the angle of arrival of the received signal. The Doppler spread is significant, and multiple Doppler scales are present in the UWA channel. Therefore, the receivers operating with only a single Doppler scale compensation perform sub-optimally. The optimal receiver should incorporate all possible Doppler scales for better performance. The receiver needs to have multiple sampling rates to incorporate all Doppler scales. It is usually done by having multiple receive channels, one for each sampling rate. It requires tremendous resources as its complexity increases exuberantly. This paper shows that these Doppler scales are clustered and that an optimal receiver is implemented using fewer receiver channels, each corresponding to one such cluster. It reduces the receiver's complexity. The simulation results demonstrate that using the Doppler scale value associated with the path of the highest magnitude per cluster yields the best performance.

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10

Zeng, Wen-Jun, and Wen Xu. "Low complexity estimation and equalization of doubly spread underwater acoustic channels." Journal of the Acoustical Society of America 131, no. 4 (2012): 3275. http://dx.doi.org/10.1121/1.4708244.

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