Deep-Learning for Generic Blind-Joint Channel Equalization and Power Amplifier Post-Distortion
Author:
Affiliation:
1. MEDIATRON Laboratory, High School of Communications of Tunis, University of Carthage, Ariana, Tunisia
2. National Conservatory of Arts and Crafts, Paris, France
3. IMT Atlantique, Lab-STICC, UMR CNRS 6285, Brest, France
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering
Link
http://xplorestaging.ieee.org/ielx7/6287639/10005208/10256031.pdf?arnumber=10256031
Reference38 articles.
1. Nonlinear blind equalization schemes using complex-valued multilayer feedforward neural networks
2. Multiple hypothesis modulation classification based on cyclic cumulants of different orders
3. Generalized Derivation of Neural Network Constant Modulus Algorithm for Blind Equalization
4. Classification of linear modulations by a combination of different orders cyclic cumulants
5. Adaptive Channel Equalization using Multilayer Perceptron Neural Networks with variable learning rate parameter
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