Wireless ultraviolet light scattering channel estimation method based on deep learning

Abstract

The invention discloses a wireless ultraviolet light scattering channel estimation method based on deep learning, and the method comprises the specific steps: firstly carrying out the modeling of a wireless ultraviolet light non-direct-view single scattering channel, calculating the related channel parameters of channel response and the like, and then carrying out the offline deep neural network training through a large amount of offline channel training data, calculating a mapping relationship between the received data and the channel response according to a training result, finally performing channel estimation by using the trained deep neural network, sending the trained channel parameters to a receiving end, inputting the received data into the deep neural network, and outputting the optimal channel response, thereby realizing channel estimation. According to the method, the problems of high bit error rate, poor robustness, requirement on prior channel characteristics and the likein a traditional channel estimation algorithm are solved, deep learning and wireless ultraviolet light communication are combined, the transceiving accuracy and reliability of a communication system are improved, and a theoretical basis is provided for further application of deep learning to optical communication.

Description

technical field [0001] The invention belongs to the field of channel estimation in optical communication systems, and in particular relates to a deep learning-based wireless ultraviolet light scattering channel estimation method. Background technique [0002] Wireless ultraviolet light communication is a wireless optical communication method that uses atmospheric scattering for information transmission. When the optical signal is transmitted into the atmosphere and encounters particles, aerosols, dust and other particles, a strong scattering effect occurs. This strong scattering characteristic is conducive to the realization of non-direct-sight communication, but this characteristic will also make wireless ultraviolet light relatively weak. Obvious signal multipath effect, this phenomenon will cause serious pulse broadening phenomenon, such as figure 2 shown. When the transmission data rate is high, the phenomenon of pulse broadening will cause intersymbol interference bet...

AI Technical Summary

Problems solved by technology

When the optical signal is transmitted into the atmosphere and encounters particles, aerosols, dust and other particles, a strong scattering effect occurs. This strong scattering characteristic is conducive to the realization of non-direct-sight communication, but this characteristic will also make wireless ultraviolet light relatively weak. Obvious signal multipath effect, this phenomenon will cause serious pulse broadening phenomenon, such as figure 2 shown

When the transmission data rate is high, the phenomenon of pulse broadening will cause intersymbol interference between information symbols, which will have a greater impact on the subsequent signal detection process and increase the bit error rate of the system

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