A novel blind subspace-based channel estimation technique is developed for direct-sequence code division multiple-access (DS-CDMA) systems operating in unknown wide-sense stationary noise environments. Unlike the existing blind algorithms designed for unknown noise environments, the proposed technique is applicable to any symbol constellation and does not require any auxiliary antennas at the receiver side. The proposed technique is based on the generalized correlation decomposition (GCD) that is used to obtain more accurate estimates of the noise subspace and the user-of-interest channel vector. Simulation results show that when the optimal GCD weighting matrices are used, the estimation performance is substantially improved as compared to the conventional singular value decomposition (SVD)-based blind channel estimation techniques.
Keyvan Zarifi, Alex B. Gershman