Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Channel Estimation via Successive Denoising in MIMO OFDM Systems: A
  Reinforcement Learning Approach   In general, reliable communication via multiple-input multiple-output (MIMO)
orthogonal frequency division multiplexing (OFDM) requires accurate channel
estimation at the receiver. The existing literature largely focuses on
denoising methods for channel estimation that depend on either (i)~channel
analysis in the time-domain with prior channel knowledge or (ii)~supervised
learning techniques which require large pre-labeled datasets for training. To
address these limitations, we present a frequency-domain denoising method based
on a reinforcement learning framework that does not need a priori channel
knowledge and pre-labeled data. Our methodology includes a new successive
channel denoising process based on channel curvature computation, for which we
obtain a channel curvature magnitude threshold to identify unreliable channel
estimates. Based on this process, we formulate the denoising mechanism as a
Markov decision process, where we define the actions through a geometry-based
channel estimation update, and the reward function based on a policy that
reduces mean squared error (MSE). We then resort to Q-learning to update the
channel estimates. Numerical results verify that our denoising algorithm can
successfully mitigate noise in channel estimates. In particular, our algorithm
provides a significant improvement over the practical least squares (LS)
estimation method and provides performance that approaches that of the ideal
linear minimum mean square error (LMMSE) estimation with perfect knowledge of
channel statistics.

8
The categories of this paper are: hep-ex
17
The categories of this paper are: q-fin
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
18
The categories of this paper are: econ
27
The categories of this paper are: comp-gas
21
The categories of this paper are: adap-org
26
The categories of this paper are: bayes-an
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
25
The categories of this paper are: patt-sol
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
15
The categories of this paper are: nucl-ex
22
The categories of this paper are: chao-dyn