In
many sea-exploration scenarios, a wireless optical communication link between
an onshore station and a floating marine structure or between a floating buoy
and an underwater vehicle is required. In order to establish high-quality
wireless optical communication, the effect of sea-waves must be taken into
consideration. In this work, we investigate the influence of surface water
waves having various amplitudes, frequencies and waveforms on the quality of an
analog speech signal transmitted over a wireless optical communication link.
Such investigation is also carried out on an encrypted speech signal. The
quality of the speech signals is determined by utilizing a deep learning neural
network that is trained to recognize ten speech commands and produces
classification probabilities. In our experiments, either the detector or the
light source is non-stationary as a result of the water-waves, thus distorting
the received analog signal. We also show a method of deriving the frequency of
the water waves by using a remote tracking unit based on
micro-electro-mechanical systems (MEMS) mirrors.
In
many sea-exploration scenarios, a wireless optical communication link between
an onshore station and a floating marine structure or between a floating buoy
and an underwater vehicle is required. In order to establish high-quality
wireless optical communication, the effect of sea-waves must be taken into
consideration. In this work, we investigate the influence of surface water
waves having various amplitudes, frequencies and waveforms on the quality of an
analog speech signal transmitted over a wireless optical communication link.
Such investigation is also carried out on an encrypted speech signal. The
quality of the speech signals is determined by utilizing a deep learning neural
network that is trained to recognize ten speech commands and produces
classification probabilities. In our experiments, either the detector or the
light source is non-stationary as a result of the water-waves, thus distorting
the received analog signal. We also show a method of deriving the frequency of
the water waves by using a remote tracking unit based on
micro-electro-mechanical systems (MEMS) mirrors.
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