Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine Learning for Wireless Connectivity and Security of
  Cellular-Connected UAVs   Cellular-connected unmanned aerial vehicles (UAVs) will inevitably be
integrated into future cellular networks as new aerial mobile users. Providing
cellular connectivity to UAVs will enable a myriad of applications ranging from
online video streaming to medical delivery. However, to enable a reliable
wireless connectivity for the UAVs as well as a secure operation, various
challenges need to be addressed such as interference management, mobility
management and handover, cyber-physical attacks, and authentication. In this
paper, the goal is to expose the wireless and security challenges that arise in
the context of UAV-based delivery systems, UAV-based real-time multimedia
streaming, and UAV-enabled intelligent transportation systems. To address such
challenges, artificial neural network (ANN) based solution schemes are
introduced. The introduced approaches enable the UAVs to adaptively exploit the
wireless system resources while guaranteeing a secure operation, in real-time.
Preliminary simulation results show the benefits of the introduced solutions
for each of the aforementioned cellular-connected UAV application use case.

21
The categories of this paper are: adap-org
35
The categories of this paper are: mtrl-th
11
The categories of this paper are: hep-lat
18
The categories of this paper are: econ
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
30
The categories of this paper are: q-alg
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
13
The categories of this paper are: quant-ph
32
The categories of this paper are: atom-ph
23
The categories of this paper are: solv-int
27
The categories of this paper are: comp-gas