Channel estimation is a fundamental operation in digital communication systems that could be done using supervised or unsu- pervised (blind) strategies. Supervised techniques estimate the channel parameters using training symbols (pilots) included in the data frame, while unsupervised methods acquire information directly from the re- ceived signals. In this paper, we compare both strategies and propose a novel hybrid channel estimation method which provides performance similar to that achieved with the supervised algorithm but using a sig- nificantly more reduced number of pilot symbols. Such a hybrid scheme uses the information obtained at the receiver during the frame synchro- nization to decide the algorithm to be used in the data retrieval.
['Adriana Dapena', 'Josmary Labrador', 'Paula Maria Castro', 'José Antonio García-Naya']
A Novel Channel Estimation Scheme Combining Adaptive Supervised and Unsupervised Algorithms