Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Deep Reinforcement Learning Based Optimization for IRS Based UAV-NOMA
  Downlink Networks   This paper investigates the application of deep deterministic policy gradient
(DDPG) to intelligent reflecting surface (IRS) based unmanned aerial vehicles
(UAV) assisted non-orthogonal multiple access (NOMA) downlink networks. The
deployment of the UAV equipped with an IRS is important, as the UAV increases
the flexibility of the IRS significantly, especially for the case of users who
have no line of sight (LoS) path to the base station (BS). Therefore, the aim
of this letter is to maximize the sum rate by jointly optimizing the power
allocation of the BS, the phase shifting of the IRS and the horizontal position
of the UAV. Because the formulated problem is not convex, the DDPG algorithm is
utilized to solve it. The computer simulation results are provided to show the
superior performance of the proposed DDPG based algorithm.

28
The categories of this paper are: alg-geom
13
The categories of this paper are: quant-ph
34
The categories of this paper are: chem-ph
23
The categories of this paper are: solv-int
8
The categories of this paper are: hep-ex
5
The categories of this paper are: gr-qc
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
30
The categories of this paper are: q-alg
12
The categories of this paper are: nucl-th
7
The categories of this paper are: hep-th
1
The categories of this paper are: cs
36
The categories of this paper are: cmp-lg
3
The categories of this paper are: physics