Robust Signal Detection in Complex Noise and Interference Environment Based on MoG Modeling

The signal detection is a key issue in the Multi-Input Multi-Output (MIMO) system. For the noise and interference environment with Gaussian distribution, many effective signal detection methods have been proposed. In the 5th generation New Radio (5G-NR) system, its high density, high frequency and l...

Full description

Saved in:
Bibliographic Details
Published in:IEEE wireless communications letters 2024-08, Vol.13 (8), p.2155-2159
Main Authors: Du, Heng, Li, Longwei, Xue, Jiang
Format: Article
Language:English
Subjects:
Gaussian distribution
Interference
Maximum likelihood detection
MIMO
mixture of Gaussian
Noise
Normal distribution
Propagation losses
Radio signals
Robustness
Signal detection
Signal generation
Vectors
Citations: Items that this one cites
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The signal detection is a key issue in the Multi-Input Multi-Output (MIMO) system. For the noise and interference environment with Gaussian distribution, many effective signal detection methods have been proposed. In the 5th generation New Radio (5G-NR) system, its high density, high frequency and large bandwidth features may lead to a complex environment (including noise and interference), whose distribution is non-Gaussian. Therefore, the robust signal detection methods in a complex environment need to be studied. The mixture of Gaussian (MoG) distribution has been proven to be able to model the complex environment with any continuous distribution. In this letter, many effective signal detection methods are extended from the assumption of Gaussian distribution to MoG distribution and can better deal with the complex environment. The numerical results confirm the superiorities of our proposed methods.
ISSN:2162-2337
2162-2345
DOI:10.1109/LWC.2024.3404012