Classification of co-channel communication signals using cyclic cumulants
ASILOMAR '95 Proceedings of the 29th Asilomar Conference on Signals, Systems and Computers (2-Volume Set)
Blind Equalization and System Identification: Batch Processing Algorithms, Performance and Applications (Advanced Textbooks in Control & Signal Processing)
Robust switching blind equalizer for wireless cognitive receivers
IEEE Transactions on Wireless Communications - Part 1
Cognitive radio: brain-empowered wireless communications
IEEE Journal on Selected Areas in Communications
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The automatic modulation classifier (AMC) is an important signal processing component that helps the cognitive radio (CR) better utilize the spectrum. In a typical CR scenario, training sequence or channel knowledge is not available, and hence blind equalizers are widely used. The multipath fading channel not only affects symbol detection performance but also affects the performance of the AMC. In a conventional single input single output blind equalizer, the weights of the equalizer are adapted by minimizing cost functions that are non quadratic (multimodal). Convergence of the blind equalizer to a local minimum affects both symbol detection performance and AMC performance. In a CR scenario, it is preferable to consider the performance of the AMC also while adapting the blind equalizer weights. In this article, we propose novel CR receivers where the performance of the AMC is also considered while adapting the parameters of the blind equalizer. Computer simulations are given to illustrate the concept and yield promising results.