Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
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 An ML-Based Estimate and the Cramer-Rao Bound for Data-Aided Channel Estimation in KSP-OFDM | Hindawi Publishing Corporation EURASIP Journal on Wireless Communications and Networking Volume 2008 Article ID 186809 9 pages doi 10.1155 2008 186809 Research Article An ML-Based Estimate and the Cramer-Rao Bound for Data-Aided Channel Estimation in KSP-OFDM Heidi Steendam Marc Moeneclaey and Herwig Bruneel The Department of Telecommunications and Information Processing TELIN Ghent University Sint-Pietersnieuwstraat 41 9000 Gent Belgium Correspondence should be addressed to Heidi Steendam hs@telin.ugent.be Received 3 May 2007 Revised 22 August 2007 Accepted 28 September 2007 Recommended by Hikmet Sari We consider the Cramer-Rao bound CRB for data-aided channel estimation for OFDM with known symbol padding KSP-OFDM . The pilot symbols used to estimate the channel are positioned not only in the guard interval but also on some of the OFDM carriers in order to improve the estimation accuracy for a given guard interval length. As the true CRB is very hard to evaluate we derive an approximate analytical expression for the CRB that is the Gaussian CRB GCRB which is accurate for large block sizes. This derivation involves an invertible linear transformation of the received samples yielding an observation vector of which a number of components are nearly independent of the unknown information-bearing data symbols. The low SNR limit of the GCRB is obtained by ignoring the presence of the data symbols in the received signals. At high SNR the GCRB is mainly determined by the observations that are nearly independent of the data symbols the additional information provided by the other observations is negligible. Both SNR limits are inversely proportional to the SNR. The GCRB is essentially independent of the FFT size and the used pilot sequence and inversely proportional to the number of pilots. For a given number of pilot symbols the CRB slightly increases with the guard interval length. Further a low complexity ML-based channel estimator is derived from the observation subset
