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Abstract
In wireless ultraviolet optical communications, noise is one of the most essential factors affecting the communication system performance. This paper presents a scheme of reducing noise in the received ultraviolet signal using wavelet transform algorithms. An effective signal-to-noise ratio (SNR) calculation method for the received signals is also proposed, and adopted by our wavelet denoising scheme so that an optimal wavelet basis function can be selected. The proposed denoising method is applied to both the ultraviolet signals generated from the multi-scattering transmission simulation model and the signals received from physical experiments, under different conditions of transceiver elevation angles and communication distances. The results show consistently that the wavelet transform algorithm can significantly improve the SNRs at the receiving end. When the wavelet basis is coif2, the best denoising effect is achieved where the improved SNR reaches 11.9925 dB on average for various physical conditions.
Highlights
Ultraviolet Communication (UVC) is a new type of wireless optical communication method [1], [2]
The algorithm is implemented to the signals generated through experiments as well as with simulations. The performance of this waveletbased algorithm is measured by the improved signal-to-noise ratio (SNR) after denoising
In order to evaluate SNRs more accurately, this paper proposes a new method to numerically calculate the SNRs of the received UV signals, which is proven to be very effective
Summary
Ultraviolet Communication (UVC) is a new type of wireless optical communication method [1], [2]. This paper proposes a new method to calculate the SNR of received UV signals, and uses this value to select an optimal wavelet basis and analyzes the denoising performance. In order to better select suitable wavelet basis functions and effectively evaluate the denoising performance on UV signals, in Section III, a new SNR calculation method is presented. Using this method, the SNRs of both experimental signals and simulated signals are evaluated and compared. R where U is the voltage amplitude of the received UV signal and R=100K is the load resistance
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