A Beamspace-Time Blind RAKE Receiver for Sectored CDMA Systems
Wireless Personal Communications: An International Journal
Adaptive MC-CDMA receiver with constrained constant modulus IQRD-RLS algorithm for MAI suppression
Signal Processing - Special section: Security of data hiding technologies
Wireless Personal Communications: An International Journal
Fast RLS-Like Algorithm for Generalized Eigendecomposition and its Applications
Journal of VLSI Signal Processing Systems
A beamforming algorithm for slow FH spread-spectrum systems
Signal Processing
Using cascade time-space processing to detect multiple target signals
Proceedings of the 2006 international conference on Wireless communications and mobile computing
Robust adaptive modified Newton algorithm for generalized eigendecomposition and its application
EURASIP Journal on Advances in Signal Processing
Adaptive generalized rake reception in DS-CDMA systems
IEEE Transactions on Wireless Communications
On the performance improvements of max-SINR equalizers in wireless communications
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
Hi-index | 754.84 |
A linear receiver for direct-sequence spread-spectrum multiple-access communication systems under the aperiodic random sequence model is considered. The receiver consists of the conventional matched filter followed by a tapped delay line with the provision of incorporating the use of antenna arrays. It has the ability of suppressing multiple-access interference (MAI) and narrowband interference in some weighted proportions, as well as combining multipath components without explicit estimation of any channel conditions. Under some specific simplified channel models, the receiver reduces to the minimum variance distortionless response beamformer, the RAKE receiver, a notch filter, or an MAI suppressor. The interference rejection capability is made possible through a suitable choice of weights in the tapped delay line. The optimal weights can be obtained by straightforward but computationally complex eigenanalysis. In order to reduce the computational complexity, a simple blind adaptive algorithm is also developed