Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Machine learning based context-predictive car-to-cloud communication
  using multi-layer connectivity maps for upcoming 5G networks   While cars were only considered as means of personal transportation for a
long time, they are currently transcending to mobile sensor nodes that gather
highly up-to-date information for crowdsensing-enabled big data services in a
smart city context. Consequently, upcoming 5G communication networks will be
confronted with massive increases in Machine-type Communication (MTC) and
require resource-efficient transmission methods in order to optimize the
overall system performance and provide interference-free coexistence with human
data traffic that is using the same public cellular network. In this paper, we
bring together mobility prediction and machine learning based channel quality
estimation in order to improve the resource-efficiency of car-to-cloud data
transfer by scheduling the transmission time of the sensor data with respect to
the anticipated behavior of the communication context. In a comprehensive field
evaluation campaign, we evaluate the proposed context-predictive approach in a
public cellular network scenario where it is able to increase the average data
rate by up to 194% while simultaneously reducing the mean uplink power
consumption by up to 54%.

0
The categories of this paper are: hep-ph
7
The categories of this paper are: hep-th
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
20
The categories of this paper are: acc-phys
27
The categories of this paper are: comp-gas
36
The categories of this paper are: cmp-lg
2
The categories of this paper are: math
5
The categories of this paper are: gr-qc
37
The categories of this paper are: supr-con
10
The categories of this paper are: q-bio
3
The categories of this paper are: physics
12
The categories of this paper are: nucl-th
24
The categories of this paper are: dg-ga