Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Supervised and Semi-Supervised Learning for MIMO Blind Detection with
  Low-Resolution ADCs   The use of low-resolution analog-to-digital converters (ADCs) is considered
to be an effective technique to reduce the power consumption and hardware
complexity of wireless transceivers. However, in systems with low-resolution
ADCs, obtaining channel state information (CSI) is difficult due to significant
distortions in the received signals. The primary motivation of this paper is to
show that learning techniques can mitigate the impact of CSI unavailability. We
study the blind detection problem in multiple-input-multiple-output (MIMO)
systems with low-resolution ADCs using learning approaches. Two methods, which
employ a sequence of pilot symbol vectors as the initial training data, are
proposed. The first method exploits the use of a cyclic redundancy check (CRC)
to obtain more training data, which helps improve the detection accuracy. The
second method is based on the perspective that the to-be-decoded data can
itself assist the learning process, so no further training information is
required except the pilot sequence. For the case of 1-bit ADCs, we provide a
performance analysis of the vector error rate for the proposed methods. Based
on the analytical results, a criterion for designing transmitted signals is
also presented. Simulation results show that the proposed methods outperform
existing techniques and are also more robust.

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The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
36
The categories of this paper are: cmp-lg
21
The categories of this paper are: adap-org
10
The categories of this paper are: q-bio
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
23
The categories of this paper are: solv-int
37
The categories of this paper are: supr-con
12
The categories of this paper are: nucl-th
26
The categories of this paper are: bayes-an
9
The categories of this paper are: nlin
8
The categories of this paper are: hep-ex
29
The categories of this paper are: funct-an
16
The categories of this paper are: stat