Comparative performance evaluation of error regularized Turbo-MIMO MMSE-SIC detectors in Gaussian channels

We evaluate the performance of a set of low complexity successive interference cancellation (SIC) detection algorithms in comparison to optimal maximum a-posteriori probability (MAP) detection and low complexity linear filter detection in a Turbo multiple-input multiple-output (Turbo-MIMO) system. W...

Full description

Saved in:
Bibliographic Details
Published in:2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) pp. 2984 - 2988
Main Authors: Krebs, Alexander, Joham, Michael, Utschick, Wolfgang
Format: Conference Proceeding
Language:English
Published: IEEE 01.04.2015
Subjects:
Complexity theory
Decoding
detection
Detectors
error propagation
Iterative decoding
MIMO
Receivers
regularization
SIC
Silicon carbide
Turbo-MIMO
ISSN:1520-6149
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:We evaluate the performance of a set of low complexity successive interference cancellation (SIC) detection algorithms in comparison to optimal maximum a-posteriori probability (MAP) detection and low complexity linear filter detection in a Turbo multiple-input multiple-output (Turbo-MIMO) system. We show that both linear and SIC soft detection algorithms perform similarly poorly for iterative receivers, even if the channel decoder output is available at the detector. We propose a low complexity combined a-priori/a-posteriori information-based error regularization technique, that improves the performance of the Turbo-MIMO design considerably. With this regularization technique, we show that a decoding gain of 2.2 dB can be achieved in an LTE compliant Turbo-MIMO receiver.
ISSN:1520-6149
DOI:10.1109/ICASSP.2015.7178518