BLIND ADAPTIVE MULTIUSER DETECTION IN MULTIPATH CDMA CHANNELS BASEDON SUBSPACE TRACKING
A blind adaptive technique for signal demodulation in multipath code-division multiple-access (CDMA) communication channels is proposed. This technique is based on signal subspace estimation. The receiver employs a bank of linear filters (decorrelating filters or linear MMSE filters) at the front end to mitigate the multiple-access interference and the multipath interference. A channel estimator is used to estimate the channel state for diversity combining. It is shown that through the use of signal subspace estimation, both the decorrelating filterbank and the linear MMSE filterbank can be obtained blindly, i.e., they can be estimated from the received signal with the prior knowledge of only the signature waveform of the desired user. Two forms of the subspace-based linear filterbanks are developed and their equivalence in terms of the interference suppression capability is established. These subspace-based blind adaptive interference suppression techniques require, at each symbol epoch, the eigenvalues and the eigenvectors of an appropriate signal subspace, which ran be obtained using computationally efficient sequential adaptive eigendecomposition (subspace tracking) algorithms. Moreover, a blind adaptive method for estimating the channel state is developed, which also produces the postcombining decision statistic as a byproduct
ADVANCED BLIND ADAPTIVE MULTI-USER DETECTOR FOR COMMUNICATIONS IN NONSTATIONARY MULTIPATH FADING CHANNEL
This paper deals with an adaptive multi-user detector for direct sequence code division multiple access (DS/CDMA) wireless communication systems, named advanced blind adaptive multi-user detector (ABA-MUD), whose main features are low complexity and joint utilization of time diversity and adaptive blind processing techniques. Differently from known blind adaptive detectors, the proposed scheme achieves remarkable performance even in critical time-varying environments by means of a suitable window reprocessing technique. The ABA-MUD avoids the use of training sequences and only needs knowledge of timing and signature waveform of the desired user, number of active users and a rough evaluation of the signal-to-interference ratio (SIR) for a proper setting of the detection algorithm. Numerical results, shown here in terms of bit error rate (BER), highlight good behavior and remarkable near-far resistance of the proposed ABA-MUD receiver with respect to different alternatives, in particular, in the case of worst fading environments.