Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Generative Adversarial Estimation of Channel Covariance in Vehicular
  Millimeter Wave Systems   Enabling highly-mobile millimeter wave (mmWave) systems is challenging
because of the huge training overhead associated with acquiring the channel
knowledge or designing the narrow beams. Current mmWave beam training and
channel estimation techniques do not normally make use of the prior beam
training or channel estimation observations. Intuitively, though, the channel
matrices are functions of the various elements of the environment. Learning
these functions can dramatically reduce the training overhead needed to obtain
the channel knowledge. In this paper, a novel solution that exploits machine
learning tools, namely conditional generative adversarial networks (GAN), is
developed to learn these functions between the environment and the channel
covariance matrices. More specifically, the proposed machine learning model
treats the covariance matrices as 2D images and learns the mapping function
relating the uplink received pilots, which act as RF signatures of the
environment, and these images. Simulation results show that the developed
strategy efficiently predicts the covariance matrices of the large-dimensional
mmWave channels with negligible training overhead.

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The categories of this paper are: hep-ph
16
The categories of this paper are: stat
23
The categories of this paper are: solv-int
36
The categories of this paper are: cmp-lg
27
The categories of this paper are: comp-gas
10
The categories of this paper are: q-bio
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
6
The categories of this paper are: astro-ph
14
The categories of this paper are: math-ph
24
The categories of this paper are: dg-ga
8
The categories of this paper are: hep-ex
30
The categories of this paper are: q-alg
37
The categories of this paper are: supr-con
11
The categories of this paper are: hep-lat