A low complexity multi-user receiver with blind channel estimation and multiple access interference (MAI) suppression is proposed for a CDMA system under multipath fading and frequency offset. The design of the receiver involves the following procedure. First, a method of joint MAI suppression and channel estimation is developed based on the generalized sidelobe canceller (GSC) technique. In particular, channel estimates are obtained blindly in the form of the effective composite signature vectors (CSV) of the users. Second, a low-complexity partially adaptive (PA) realization of the receiver is proposed which incorporates reduced-rank processing based on the information of multi-user CSV's. By a judiciously designed decorrelating procedure, a new PA receiver is obtained with a much lower complexity. Finally, pilot symbols assisted frequency offset estimation and channel gain compensation give the estimate of users' symbols. Further performance enhancement is achieved by a decision aided scheme in which the signal is reconstructed and subtracted from the receiver input data, leading to significantly faster convergence. The proposed receiver is shown to be robust to multipath fading and frequency offset, and achieves nearly the same performance of the optimal maximum SINR and MMSE receivers with a much lower overhead for pilot symbols.

A reduced complexity multiple-input multiple-output (MIMO) equalizer with ordered successive interference cancellation (OSIC) is proposed for combating intersymbol interference (ISI) and cochannel interference (CCI) over frequency-selective multipath channels. It is developed as a reduced-rank realization of the conventional MMSE decision feedback equalizer (DFE). In particular, the MMSE weight vectors at each stage of OSIC are computed based on the generalized sidelobe canceller (GSC) technique and reduced-rank processing is incorporated by using the conjugate gradient (CG) algorithm for reduced complexity implementation. The CG algorithm leads to a best low-rank representation of the GSC blocking matrix via an iterative procedure, which in turn gives a reduced-rank equalizer weight vector achieving the best compromise between ISI and CCI suppression. With the dominating interference successfully cancelled at each stage of OSIC, the number of iterations required for the convergence of the CG algorithm decreases accordingly for the desired signal. Computer simulations demonstrate that the proposed reduced-rank MIMO DFE can achieve nearly the same performance as the full-rank MIMO MMSE DFE with an effective rank much lower than the dimension of the signal-plus-interference subspace.