MIMO Modulation Classification in Fading Channels withpplications to CR Systems
Date Issued
2009
Date
2009
Author(s)
Chao, Chin-Ting
Abstract
Modulation classification is to blindly identify the modulation type of the received signals within a set of known constellations. Although modulation classification has been researched for many years, less attention has been paid to classifying the modulation type for systems with multiple transmit antennas. In addition, recently many papers about modulation classification have been published for Cognitive Radio (CR) systems. With the knowledge ofhe modulation type that the primary (licensed) user uses, the CR user can either communicate with or avoid interfering primary users. We propose a classifier for a system with two transmit antennas in fading channels. This classifier has the ability to determine whether someone is using the channel or not. If the channel is used, the classifier can determine the modulation type and whether theser is using Alamouti Code or Vertical Bell Laboratories Layered Space-Time (V-BLAST). We use Average Likelihood Ratio Test (ALRT) approach to overcome the problem of unknown channel gains and Maximum Likelihood (ML) principle to determine the case that the CR user encounters. Simulation results show that the proposed classifier has high accuracy even at low SNR. We also extend this algorithm to the case of multiple receive antennas. To reduce the implementation complexity, two additional algorithms are proposed.
Subjects
modulation
modulation classification
cognitive radio (CR)
multiple-input multiple-outputl (MIMO)
Alamouti Code
V-BLAST
average likelihood ratio test (ALRT)
Type
thesis
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