Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Learning based signal detection for MIMO systems with unknown noise
  statistics   This paper aims to devise a generalized maximum likelihood (ML) estimator to
robustly detect signals with unknown noise statistics in multiple-input
multiple-output (MIMO) systems. In practice, there is little or even no
statistical knowledge on the system noise, which in many cases is non-Gaussian,
impulsive and not analyzable. Existing detection methods have mainly focused on
specific noise models, which are not robust enough with unknown noise
statistics. To tackle this issue, we propose a novel ML detection framework to
effectively recover the desired signal. Our framework is a fully probabilistic
one that can efficiently approximate the unknown noise distribution through a
normalizing flow. Importantly, this framework is driven by an unsupervised
learning approach, where only the noise samples are required. To reduce the
computational complexity, we further present a low-complexity version of the
framework, by utilizing an initial estimation to reduce the search space.
Simulation results show that our framework outperforms other existing
algorithms in terms of bit error rate (BER) in non-analytical noise
environments, while it can reach the ML performance bound in analytical noise
environments. The code of this paper is available at
https://github.com/skypitcher/manfe.

18
The categories of this paper are: econ
10
The categories of this paper are: q-bio
23
The categories of this paper are: solv-int
32
The categories of this paper are: atom-ph
13
The categories of this paper are: quant-ph
19
The categories of this paper are: eess
27
The categories of this paper are: comp-gas
30
The categories of this paper are: q-alg
3
The categories of this paper are: physics
31
The categories of this paper are: ao-sci
35
The categories of this paper are: mtrl-th
33
The categories of this paper are: plasm-ph
22
The categories of this paper are: chao-dyn
11
The categories of this paper are: hep-lat
17
The categories of this paper are: q-fin
37
The categories of this paper are: supr-con