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We have previously analysed the performance of the totally blind estimation method [10]. In the present paper we develop a novel pseudo-blind algorithm based on the same estimation principle, but now using the training sequences to initialise the estimation. The reason to focus on the pseudo-blind methods instead of the totally blind estimation is twofold. First, with the SDMA application, when more than one users are served simultaneously in the same traffic channel, some kind of known information must be included in the transmitted signals.

With the blind algorithms we are not making beamforming in the traditional sense but we are only collecting samples in the space and/or time domains allowing the separation of the signals. Thus, we do not need so precisely steered beam patterns requiring a larger number of the antenna elements. This naturally leads to reduced hardware costs. 6)If we consider totally blind methods, they offer also an additional capacity increase assuming that their use is included in the forthcoming standards. We need less overhead information which is required for the channel estimation purposes with conventional techniques.

We are only separating the signals based on their different channel responses, without estimating any directional information. 2)The blind methods are robust against receiver imperfections and they do not set strict requirements for the calibration of the array. With blind methods we only collect several samples of the signal in the space and/or time domain, without assuming anything about the array geometry. 3)The whole detection process is performed simultaneously using the same blind estimation principle.