Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Beyond 5G: Leveraging Cell Free TDD Massive MIMO using Cascaded Deep
  learning   This paper deals with the calibration of Time Division Duplexing (TDD)
reciprocity in an Orthogonal Frequency Division Multiplexing (OFDM) based Cell
Free Massive MIMO system where the responses of the (Radio Frequency) RF chains
render the end to end channel non-reciprocal, even though the physical wireless
channel is reciprocal. We further address the non-availability of the uplink
channel estimates at locations other than pilot subcarriers and propose a
single-shot solution to estimate the downlink channel at all subcarriers from
the uplink channel at selected pilot subcarriers. We propose a cascade of two
Deep Neural Networks (DNN) to achieve the objective. The proposed method is
easily scalable and removes the need for relative reciprocity calibration based
on the cooperation of antennas, which usually introduces dependency in Cell
Free Massive MIMO systems.

37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
15
The categories of this paper are: nucl-ex
8
The categories of this paper are: hep-ex
28
The categories of this paper are: alg-geom
29
The categories of this paper are: funct-an
25
The categories of this paper are: patt-sol
27
The categories of this paper are: comp-gas
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th
5
The categories of this paper are: gr-qc
31
The categories of this paper are: ao-sci
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
14
The categories of this paper are: math-ph
22
The categories of this paper are: chao-dyn