Tuyển tập báo cáo các nghiên cứu khoa học quốc tế ngành hóa học dành cho các bạn yêu hóa học tham khảo đề tài: Research Article Superimposed Training-Based Joint CFO and Channel Estimation for CP-OFDM Modulated Two-Way Relay Networks | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2010 Article ID 403936 9 pages doi 2010 403936 Research Article Superimposed Training-Based Joint CFO and Channel Estimation for CP-OFDM Modulated Two-Way Relay Networks Gongpu Wang 1 Feifei Gao 2 Xin Zhang 3 and Chintha Tellambura1 1 Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada T6G 2V4 2School of Engineering and Science Jacobs University 28759 Bremen Germany 3School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China Correspondence should be addressed to Gongpu Wang gongpu@ Received 30 January 2010 Revised 23 May 2010 Accepted 16 June 2010 Academic Editor Petar Popovski Copyright 2010 Gongpu Wang et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. Joint carrier frequency offset CFO and channel estimation is considered for two-way relay networks TWRNs . Existing estimators provide only the convolved channel parameters and the mixed CFO values. In contrast estimators using a superimposed training strategy are developed for the individual frequency and channel parameters. Depending on the number of pilots three different estimators are developed. An iterative estimator with low complexity is also developed to further improve the estimation accuracy. The Cramer-Rao Bounds CRBs are derived. The simulations show that the iterative estimator converges rapidly and the resultant estimation mean square error MSE approaches the CRB. For the special case of small CFO between the two source terminals the MSE achieves the CRB at high SNRs and the iterative algorithm is not necessary. However for the general case the gap between the MSE and the CRB indicates that there is room for further .
