Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Training for Channel Estimation in Nonlinear Multi-Antenna Transceivers   Recent efforts to obtain high data rates in wireless systems have focused on
what can be achieved in systems that have nonlinear or coarsely quantized
transceiver architectures. Estimating the channel in such a system is
challenging because the nonlinearities distort the channel estimation process.
It is therefore of interest to determine how much training is needed to
estimate the channel sufficiently well so that the channel estimate can be used
during data communication. We provide a way to determine how much training is
needed by deriving a lower bound on the achievable rate in a training-based
scheme that can be computed and analyzed even when the number of antennas is
very large. This lower bound can be tight, especially at high SNR. One
conclusion is that the optimal number of training symbols may paradoxically be
smaller than the number of transmitters for systems with coarsely-quantized
transceivers. We show how the training time can be strongly dependent on the
number of receivers, and give an example where doubling the number of receivers
reduces the training time by about 37 percent.

34
The categories of this paper are: chem-ph
37
The categories of this paper are: supr-con
4
The categories of this paper are: cond-mat
10
The categories of this paper are: q-bio
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
31
The categories of this paper are: ao-sci
15
The categories of this paper are: nucl-ex
24
The categories of this paper are: dg-ga
35
The categories of this paper are: mtrl-th
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
6
The categories of this paper are: astro-ph
29
The categories of this paper are: funct-an
9
The categories of this paper are: nlin
19
The categories of this paper are: eess