Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: AirNet: Neural Network Transmission over the Air   State-of-the-art performance for many emerging edge applications is achieved
by deep neural networks (DNNs). Often, the employed DNNs are location- and
time-dependent, and the parameters of a specific DNN must be delivered from an
edge server to the edge device rapidly and efficiently to carry out
time-sensitive inference tasks. This can be considered as a joint
source-channel coding (JSCC) problem, in which the goal is not to recover the
DNN coefficients with the minimal distortion, but in a manner that provides the
highest accuracy in the downstream task. For this purpose we introduce AirNet,
a novel training and analog transmission method to deliver DNNs over the air.
We first train the DNN with noise injection to counter the wireless channel
noise. We also employ pruning to identify the most significant DNN parameters
that can be delivered within the available channel bandwidth, knowledge
distillation, and non-linear bandwidth expansion to provide better error
protection for the most important network parameters. We show that AirNet
achieves significantly higher test accuracy compared to the separation-based
alternative, and exhibits graceful degradation with channel quality.

17
The categories of this paper are: q-fin
25
The categories of this paper are: patt-sol
2
The categories of this paper are: math
23
The categories of this paper are: solv-int
0
The categories of this paper are: hep-ph
30
The categories of this paper are: q-alg
5
The categories of this paper are: gr-qc
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
6
The categories of this paper are: astro-ph
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci