Abstract
Adaptive modulation and automatic modulation classification are highly demanded in software-defined radio (SDR) for both commercial and military applications. Various design options of automatic classifiers have attracted researchers in developing 3G and 4G wireless communication systems. There is an urgent need to investigate the different methods of coherent and noncoherent modulation estimations, discuss the challenges in cooperative and noncooperative communication environment, and understand the distinct requirements in real-time modulation classifications. This survey paper focuses on the automatic modulation classification methods based on likelihood functions, studies various classification solutions derived from likelihood ratio test, and discusses the detailed characteristics associated with all major algorithms.
Original language | English (US) |
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Article number | 5606206 |
Pages (from-to) | 455-469 |
Number of pages | 15 |
Journal | IEEE Transactions on Systems, Man and Cybernetics Part C: Applications and Reviews |
Volume | 41 |
Issue number | 4 |
DOIs | |
State | Published - Jul 2011 |
All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Information Systems
- Human-Computer Interaction
- Computer Science Applications
- Electrical and Electronic Engineering
Keywords
- Cognitive radio
- likelihood ratio test (LRT)
- maximum likelihood (ML)
- modulation classification
- modulation recognition
- software-defined radio (SDR)
- wireless communication systems