Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: An Introduction to Deep Learning for the Physical Layer   We present and discuss several novel applications of deep learning for the
physical layer. By interpreting a communications system as an autoencoder, we
develop a fundamental new way to think about communications system design as an
end-to-end reconstruction task that seeks to jointly optimize transmitter and
receiver components in a single process. We show how this idea can be extended
to networks of multiple transmitters and receivers and present the concept of
radio transformer networks as a means to incorporate expert domain knowledge in
the machine learning model. Lastly, we demonstrate the application of
convolutional neural networks on raw IQ samples for modulation classification
which achieves competitive accuracy with respect to traditional schemes relying
on expert features. The paper is concluded with a discussion of open challenges
and areas for future investigation.

18
The categories of this paper are: econ
16
The categories of this paper are: stat
20
The categories of this paper are: acc-phys
33
The categories of this paper are: plasm-ph
17
The categories of this paper are: q-fin
21
The categories of this paper are: adap-org
19
The categories of this paper are: eess
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
12
The categories of this paper are: nucl-th
36
The categories of this paper are: cmp-lg
37
The categories of this paper are: supr-con
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin