Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Probabilistic MIMO Symbol Detection with Expectation Consistency
  Approximate Inference   In this paper we explore low-complexity probabilistic algorithms for soft
symbol detection in high-dimensional multiple-input multiple-output (MIMO)
systems. We present a novel algorithm based on the Expectation Consistency (EC)
framework, which describes the approximate inference problem as an optimization
over a non-convex function. EC generalizes algorithms such as Belief
Propagation and Expectation Propagation. For the MIMO symbol detection problem,
we discuss feasible methods to find stationary points of the EC function and
explore their tradeoffs between accuracy and speed of convergence. The accuracy
is studied, first in terms of input-output mutual information and show that the
proposed EC MIMO detector greatly improves state-of-the-art methods, with a
complexity order cubic in the number of transmitting antennas. Second, these
gains are corroborated by combining the probabilistic output of the EC detector
with a low-density parity-check (LDPC) channel code.

16
The categories of this paper are: stat
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
35
The categories of this paper are: mtrl-th
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
4
The categories of this paper are: cond-mat
18
The categories of this paper are: econ
32
The categories of this paper are: atom-ph
37
The categories of this paper are: supr-con
26
The categories of this paper are: bayes-an
8
The categories of this paper are: hep-ex
24
The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
11
The categories of this paper are: hep-lat
30
The categories of this paper are: q-alg