CLC number: TP391.4
On-line Access: 2024-08-27
Received: 2023-10-17
Revision Accepted: 2024-05-08
Crosschecked: 2019-10-10
Cited: 0
Clicked: 7565
Maqsood H. SHAH; Xiao-yu DANG. An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems[J]. Frontiers of Information Technology & Electronic Engineering, 2020, 21(3): 465-475.
@article{title="An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems",
author="Maqsood H. SHAH; Xiao-yu DANG",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="21",
number="3",
pages="465-475",
year="2020",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.1800306"
}
%0 Journal Article
%T An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems
%A Maqsood H. SHAH
%A Xiao-yu DANG
%J Frontiers of Information Technology & Electronic Engineering
%V 21
%N 3
%P 465-475
%@ 2095-9184
%D 2020
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.1800306
TY - JOUR
T1 - An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems
A1 - Maqsood H. SHAH
A1 - Xiao-yu DANG
J0 - Frontiers of Information Technology & Electronic Engineering
VL - 21
IS - 3
SP - 465
EP - 475
%@ 2095-9184
Y1 - 2020
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.1800306
Abstract: A low-complexity likelihood methodology is proposed for automatic modulation classification of orthogonal space-time block code (STBC) based multiple-input multiple-output (MIMO) systems. We exploit the zero-forcing equalization technique to modify the typical average likelihood ratio test (ALRT) function. The proposed ALRT function has a low computational complexity compared to existing ALRT functions for MIMO systems classification. The proposed approach is analyzed for blind channel scenarios when the receiver has imperfect channel state information (CSI). Performance analysis is carried out for scenarios with different numbers of antennas. Alamouti-STBC systems with 2×2 and 2×1 and space-time transmit diversity with a 4×4 transmit and receive antenna configuration are considered to verify the proposed approach. Some popular modulation schemes are used as the modulation test pool. Monte-Carlo simulations are performed to evaluate the proposed methodology, using the probability of correct classification as the criterion. Simulation results show that the proposed approach has high classification accuracy at low signal-to-noise ratios and exhibits robust behavior against high CSI estimation error variance.
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