Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Latency Fairness Optimization on Wireless Networks through Deep
  Reinforcement Learning   In this paper, we propose a novel deep reinforcement learning framework to
maximize user fairness in terms of delay. To this end, we devise a new version
of the modified largest weighted delay first (M-LWDF) algorithm, which is
called $\beta$-M-LWDF, aiming to fulfill an appropriate balance between user
fairness and average delay. This balance is defined as a feasible region on the
cumulative distribution function (CDF) of the user delay that allows
identifying unfair states, feasible-fair states, and over-fair states.
Simulation results reveal that our proposed framework outperforms traditional
resource allocation techniques in terms of latency fairness and average delay

5
The categories of this paper are: gr-qc
27
The categories of this paper are: comp-gas
6
The categories of this paper are: astro-ph
30
The categories of this paper are: q-alg
28
The categories of this paper are: alg-geom
37
The categories of this paper are: supr-con
36
The categories of this paper are: cmp-lg
12
The categories of this paper are: nucl-th
10
The categories of this paper are: q-bio
26
The categories of this paper are: bayes-an
22
The categories of this paper are: chao-dyn
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
32
The categories of this paper are: atom-ph
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The categories of this paper are: eess
23
The categories of this paper are: solv-int