Closed-form blind channel identification and source separation in SDMA systems through correlative coding. - Xavier, J.M.F.
We address the problem of blind identification of multiuser multiple-input multiple-output (MIMO) finite-impulse response (FIR) digital systems. This problem arises in spatial division multiple access (SDMA) architectures for wireless communications. We present a closed-form, i.e., noniterative, consistent estimator for the MIMO channel based only on second-order statistics. To obtain this closed form we introduce spectral/correlation asymmetry between the sources by filtering each source output with adequate correlative filters. Our algorithm uses the closed form MIMO channel estimate to cancel the intersymbol interference (ISI) due to multipath propagation and to discriminate between the sources at the wireless base station receiver. Simulation results show that, for single-user channels, this technique yields better channel estimates in terms of mean-square error (MSE) and better probability of error than a well-known alternative method. Finally, we illustrate its performance for MIMO channels in the context of the global system for mobile communications (GSM) system
Keywords: FIR digital systems; GSM system; ISI cancellation; MSE; SDMA systems; Closed form MIMO channel estimate; Closed-form blind channel identification; Closed-form estimator; Correlative coding; Correlative filters; Error probability; Finite-impulse response; Global system for mobile communications; Intersymbol interference; Mean-square error; Multipath propagation; Multiuser multiple-input multiple-output system; Noniterative consistent estimator; Second-order statistics; Simulation results; Single-user channels; Source output filtering; Source separation; Spatial division multiple access; Spectral/correlation asymmetry; Wireless base station receiver; Wireless communications