Title :
Improved Carrier Frequency Offset Estimation using Data-Dependent Superimposed Training
Author :
Moosvi, S.M.A. ; McLernon, D.C. ; Orozco-Lugo, A.G. ; Lara, M.M. ; Alameda-Hernandez, E.
Author_Institution :
Univ. of Leeds, Leeds
Abstract :
rdquoWe address the problem of carrier frequency offset (CFO) estimation within the Data Dependent Superimposed Training (DDST) framework for channel estimation. A CFO estimator was recently developed for DDST, which uses two different data dependent training sequences, one for CFO estimation and other for channel estimation. Here, we propose a CFO estimation scheme which combines the estimates using both the data-dependent training sequences to improve the performance. Finally, simulations are presented that verify the theoretical developments.
Keywords :
channel estimation; frequency estimation; CFO estimator; DDST framework; carrier frequency offset estimation; channel estimation; data-dependent superimposed training; Bandwidth; Channel estimation; Cities and towns; Data engineering; Digital communication; Fading; Frequency estimation; Interference; Time division multiplexing; Transmitters; Frequency estimation; frequency selective fading; superimposed training;
Conference_Titel :
Electrical and Electronics Engineering, 2007. ICEEE 2007. 4th International Conference on
Conference_Location :
Mexico City
Print_ISBN :
978-1-4244-1166-5
Electronic_ISBN :
978-1-4244-1166-5
DOI :
10.1109/ICEEE.2007.4344990
