Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Channel Estimation for Intelligent Reflecting Surface Assisted
  Backscatter Communication   Intelligent reflecting surface (IRS) is a promising technology to improve the
performance of backscatter communication systems by smartly reconfiguring the
multi-reflection channel. To fully exploit the passive beamforming gain of IRS
in backscatter communication, channel state information (CSI) is indispensable
but more practically challenging to acquire than conventional IRS-assisted
systems, since IRS passively reflects signals over both the forward and
backward (backscattering) links between the reader and tag. To address this
issue, we propose in this letter a new and efficient channel estimation scheme
for the IRS-assisted backscatter communication system. To minimize the
mean-square error (MSE) of channel estimation, we formulate and solve an
optimization problem by designing the IRS training reflection matrix for
channel estimation under the constraints of unit-modulus elements and full
rank. Simulation results verify the effectiveness of the proposed channel
estimation scheme as compared to other baseline schemes.

30
The categories of this paper are: q-alg
22
The categories of this paper are: chao-dyn
15
The categories of this paper are: nucl-ex
10
The categories of this paper are: q-bio
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
20
The categories of this paper are: acc-phys
31
The categories of this paper are: ao-sci
4
The categories of this paper are: cond-mat
33
The categories of this paper are: plasm-ph
19
The categories of this paper are: eess
34
The categories of this paper are: chem-ph
27
The categories of this paper are: comp-gas
12
The categories of this paper are: nucl-th
25
The categories of this paper are: patt-sol
14
The categories of this paper are: math-ph