TY - GEN
T1 - Low complexity space-frequency rake receivers for WCDMA
AU - Brunnerr, Christopher
AU - Haardt, Martin
AU - Nossek, Josef A.
N1 - Publisher Copyright:
© 1999 IEEE.
PY - 1999
Y1 - 1999
N2 - Adaptive space-frequency rake receivers use diversity combining and multi-user interference suppression to obtain a considerable increase in performance in DS-CDMA-systems such as WCDMA. The main advantages of operation in the space-frequency domain include a reduced computational complexity and an improved noise suppression. To this end, the signal-plus-interference-and-noise (SIN) and the interference-plus-noise (IN) space-frequency covariance matrices are required-The optimum weight vector for symbol decisions is the "largest" generalized eigenvector of the resulting matrix pencil. If we decouple spatial and frequency processing with respect to interferingj users, the IN space-frequency covariance matrix can be approximated by the Kronecker product of the frequency and the spatial covariance' matrix. Then this IN covariance matrix is estimated by using the outputs of the antenna elements before correlation and the output of the conventional rake fingers of the antenna elements may be utilized to approximate the SIN covariance matrix. Thus, the required correlations are reduced to the number of rake fingers. Moreover, the computational complexity which is required to estimate the optimum weight vector may be reduced significantly.
AB - Adaptive space-frequency rake receivers use diversity combining and multi-user interference suppression to obtain a considerable increase in performance in DS-CDMA-systems such as WCDMA. The main advantages of operation in the space-frequency domain include a reduced computational complexity and an improved noise suppression. To this end, the signal-plus-interference-and-noise (SIN) and the interference-plus-noise (IN) space-frequency covariance matrices are required-The optimum weight vector for symbol decisions is the "largest" generalized eigenvector of the resulting matrix pencil. If we decouple spatial and frequency processing with respect to interferingj users, the IN space-frequency covariance matrix can be approximated by the Kronecker product of the frequency and the spatial covariance' matrix. Then this IN covariance matrix is estimated by using the outputs of the antenna elements before correlation and the output of the conventional rake fingers of the antenna elements may be utilized to approximate the SIN covariance matrix. Thus, the required correlations are reduced to the number of rake fingers. Moreover, the computational complexity which is required to estimate the optimum weight vector may be reduced significantly.
UR - http://www.scopus.com/inward/record.url?scp=84948160197&partnerID=8YFLogxK
U2 - 10.1109/APS.1999.789506
DO - 10.1109/APS.1999.789506
M3 - Conference contribution
AN - SCOPUS:84948160197
T3 - IEEE Antennas and Propagation Society International Symposium: Wireless Technologies and Information Networks, APS 1999 - Held in conjunction with USNC/URSI National Radio Science Meeting
SP - 1104
EP - 1107
BT - IEEE Antennas and Propagation Society International Symposium
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1999 IEEE Antennas and Propagation Society International Symposium, APSURSI 1999
Y2 - 11 July 1999 through 16 July 1999
ER -