Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Reinforcement Learning for Self-Organization and Power Control of
  Two-Tier Heterogeneous Networks   Self-organizing networks (SONs) can help manage the severe interference in
dense heterogeneous networks (HetNets). Given their need to automatically
configure power and other settings, machine learning is a promising tool for
data-driven decision making in SONs. In this paper, a HetNet is modeled as a
dense two-tier network with conventional macrocells overlaid with denser small
cells (e.g. femto or pico cells). First, a distributed framework based on
multi-agent Markov decision process is proposed that models the power
optimization problem in the network. Second, we present a systematic approach
for designing a reward function based on the optimization problem. Third, we
introduce Q-learning based distributed power allocation algorithm (Q-DPA) as a
self-organizing mechanism that enables ongoing transmit power adaptation as new
small cells are added to the network. Further, the sample complexity of the
Q-DPA algorithm to achieve $\epsilon$-optimality with high probability is
provided. We demonstrate, at density of several thousands femtocells per
km$^2$, the required quality of service of a macrocell user can be maintained
via the proper selection of independent or cooperative learning and appropriate
Markov state models.

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The categories of this paper are: plasm-ph
6
The categories of this paper are: astro-ph
23
The categories of this paper are: solv-int
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The categories of this paper are: supr-con
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The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
14
The categories of this paper are: math-ph
26
The categories of this paper are: bayes-an
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
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The categories of this paper are: stat
4
The categories of this paper are: cond-mat
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The categories of this paper are: adap-org
10
The categories of this paper are: q-bio