Noise Reduction on Received Signals in Wireless Ultraviolet Communications Using Wavelet Transform

Song, Peng; Tan, Yumei; Geng, Xiaojun; Zhao, Taifei

doi:10.1109/access.2020.3009944

Cited by 13 publications

(5 citation statements)

References 29 publications

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“…Wavelet transformation provides localization in both the time and frequency domains by calculating wavelet coe cients through the convolution of the observed signals and a wavelet [15,16]. Wavelet-based de-noising algorithms are typically better than classical de-noising algorithms [17]. Because wavelet thresholding algorithms are straightforward and simple to implement, they have been widely used for noise reduction [18,19].…”

Section: Brief Literature Reviewmentioning

confidence: 99%

Discrete Wavelet Transform and Spectral Subtraction Based Speech Enhancement Algorithm for Hearing Aid Application

Iqbal,

Zhang,

Geng

et al. 2024

Preprint

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Hearing aids are small electronic devices intended to help those with hearing loss improve their hearing ability with the use of advanced audio signal processing techniques and technologies. Usually, in hearing aids, a set of speech enhancement methods are utilized to improve speech signal quality in low signal-to-noise ratio (SNR) environments. In speech processing, Discrete Wavelet Transform (DWT) algorithm and Spectral Subtraction (SS) filter are some of the most commonly used methods today when handling background noise in hearing aids. However, these speech enhancement systems have drawbacks like in DWT, the selective thresholding face problems when applying to distinct types of noise with different frequencies and time scales, and spectral subtraction has a problem with music noise, which affects the denoising performance. In this paper, the Spectral Subtraction (SS) filter and DWT speech enhancement methods are combined to deal with problem faced by DWT selective thresholding techniques against noise of different frequencies and time scales and the musical noise faced by the spectral subtraction filter. We first used spectral subtraction to reduce average noise intensity and then added DWT thresholding for reducing the background noise further. The contemporary methods evaluated using English speech signals taken from CSTR VCTK Corpus database. The objective metrics used to evaluate proposed speech enhancement systems are MSE, SNR, PESQ, and STOI. The proposed speech enhancement algorithm is applied for noise reduction and then compared with conventional algorithms. Experimental results prove that using of the proposed speech enhancement algorithm reduces background noise, improves the SNR of an original speech signal, and improves the final noise reduction performance.

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Section: Brief Literature Reviewmentioning

confidence: 99%

Discrete Wavelet Transform and Spectral Subtraction Based Speech Enhancement Algorithm for Hearing Aid Application

Iqbal,

Zhang,

Geng

et al. 2024

Preprint

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“…when T p ¼ T R , and the value of y Q is obtained as E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 1 9 ; 1 1 6 ; 1 2 9 20) 118102-6 November 2022 • Vol. 61 (11) E Q -T A R G E T ; t e m p : i n t r a l i n k -; e 0 2 1 ; 1 1 6 ; 7 2 3…”

Section: Transmission Characteristics Of Turbulence Channel With Movi...mentioning

confidence: 99%

“…Researchers have conducted extensive studies on short-range UV communication channel modeling, including the closed approximation model, 1 , 2 single scattering model in spherical coordinate system, 3 , 4 Monte Carlo elevation difference model, 5 and UV multiple scattering model 6 , 7 . Using these models, researchers have studied the UV channel characteristics, including the communication link performance with a bit error rate (BER) lower than 10−3 under solar blind and NLOS conditions, 8 path loss of the UV scattering channel under fog and haze weather conditions, 9 verification of UV pulse broadening in NLOS communication channels, 10 noise reduction of received signals in wireless UV communication systems, 11 , 12 etc. The above works have helped to promote the development of short-range UV communication.…”

Section: Introductionmentioning

confidence: 99%

Effect of atmospheric turbulent on mobile ultraviolet wireless communications

et al. 2022

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This paper proposes a method to study the transmission characteristics of ultraviolet turbulent channels, by considering the variation of atmospheric refractive index structure parameters along transmission paths. This method is adopted in a Monte Carlo simulation to analyze the transmission characteristics of ultraviolet light when the communication nodes are mobile. The analysis focuses on the influence of the moving speed and direction of the receiver on path loss under long-distance and atmospheric turbulence conditions. The simulation results show that, when the altitude increases, atmospheric refractive index structure parameters show a decreasing trend, and the path loss of the system decreases. With or without turbulence, when the receiver moves away from the transmitter in a horizontal plane, the received signal strength always decreases as the moving speed increases; and vice versa. When the receiver moves along the vertical axis, the signal strength increases as the moving speed increases. With the presence of atmospheric turbulence, the received signal strength attenuates significantly, compared with the case with no turbulence. When the receiver moves along the vertical axis, the path loss is higher compared with the situation when the receiver moves on the horizontal plane.

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“…Additive white Gaussian noise level estimation is a fundamental process in many fields, such as biomedical signal processing [1], [2], communication system [3], [4] and image processing [5], [6]. Removing this unavoidable noise is an essential step prior to any farther processing in these systems.…”

Section: Introductionmentioning

confidence: 99%

Field programmable gate arrays implementation of different standard deviation estimation techniques

Bamerni

Alsulaifanie

2022

IJEECS

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Additive white Gaussian noise level estimation has found its application in many fields such as biomedical signal processing, communication system, and image processing. Many methods have been proposed with different output accuracy, system complexity, power consumption, and speed. In this paper, three of the most well-known and largely used algorithms (median based, root mean square (RMS) based, and P84 based methods) have been implemented and investigated in a full comparison between them to find their advantage and disadvantage, and the suitability of each method for a specific application. The three designs are created using Xilinx system generator (XSG) and implemented on Xilinx field programmable gate arrays (FPGA) development board with Zynq series "XC7Z020-1CLG484", to evaluate the design's performance and the results are discussed in the paper.

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Noise Reduction on Received Signals in Wireless Ultraviolet Communications Using Wavelet Transform

Cited by 13 publications

References 29 publications

Discrete Wavelet Transform and Spectral Subtraction Based Speech Enhancement Algorithm for Hearing Aid Application

Discrete Wavelet Transform and Spectral Subtraction Based Speech Enhancement Algorithm for Hearing Aid Application

Effect of atmospheric turbulent on mobile ultraviolet wireless communications

Field programmable gate arrays implementation of different standard deviation estimation techniques

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