An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems

Maqsood H SHAH; Xiao-yu DANG

doi:10.1631/FITEE.1800306

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An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems

Regular Papers | Updated：2022-05-19

- An effective approach for low-complexity maximum likelihood based automatic modulation classification of STBC-MIMO systems
- 基于低复杂度最大似然的STBC-MIMO系统高效调制识别方法
- Frontiers of Information Technology & Electronic Engineering Vol. 21, Issue 3, Pages: 465-475(2020)
- Affiliations：
  
  College of Electronic and Information Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 211106, China
- Author bio：
  
  Maqsood H.SHAH, E-mail:maqsood@nuaa.edu.cn
- Funds：
- DOI：10.1631/FITEE.1800306
  CLC： TP391.4
- Received：16 March 2018，
  
  Revised：2019-10-10，
  
  Published Online：27 December 2019，
  
  Published：2020-03
- Accepted：
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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.
DOI：

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. DOI： 10.1631/FITEE.1800306.

摘要

针对正交空时块编码的多输入多输出系统（STBC-MIMO），提出一种基于低复杂度似然比的自动调制识别方法。使用迫零均衡技术修正平均似然比检验函数（ALRT）。与目前MIMO系统调制识别中使用的ALRT相比，本文提出的检验函数具有较低计算复杂度。在接收机具有非理想信道状态信息的条件下，对提出的方法在盲信道场景中进行分析。同时对不同天线数目的场景进行性能分析，利用Alamouti-STBC系统（2×2与2×1）和空时发射分集（4×4）的不同发射和接收天线配置验证本文所提方法，其中一些常用的调制方式被用作调制测试池。以正确识别率为指标，采用蒙特卡罗仿真法评价本文方法。仿真结果表明，该方法在低信噪比下有较好分类精度，在信道状态信息估计误差方差大的情况下有较好稳健性。

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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