Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Data-Driven State Estimation for Light-Emitting Diode Underwater Optical
  Communication   Light-Emitting Diodes (LEDs) based underwater optical wireless communications
(UOWCs), a technology with low latency and high data rates, have attracted
significant importance for underwater robots. However, maintaining a controlled
line of sight link between transmitter and receiver is challenging due to the
constant movement of the underlying optical platform caused by the dynamic
uncertainties of the LED model and vibration effects. Additionally, the
alignment angle required for tracking is not directly measured and has to be
estimated. Besides, the light scattering propagates beam pulse in water
temporally, resulting in time-varying underwater optical links with
interference. We address the state estimation problem by designing an LED
communication system that provides the angular position and velocity
information to overcome the challenges. In this way, we leverage the power of
deep learning-based observer design to explore the LED communication's state
space properly. Simulation results are presented to illustrate the performance
of the data-driven LED state estimation.

18
The categories of this paper are: econ
5
The categories of this paper are: gr-qc
6
The categories of this paper are: astro-ph
31
The categories of this paper are: ao-sci
27
The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
17
The categories of this paper are: q-fin
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
30
The categories of this paper are: q-alg
23
The categories of this paper are: solv-int
29
The categories of this paper are: funct-an