Pilot-aided ML schemes for joint beamforming and channel estimation in WCDMA systems

This paper proposes semi-blind channel estimation and interference cancellation schemes for the reception of pilot-aided signals in WCDMA systems. It is shown that the performance of classical training-based schemes is severely degraded due to the code-multiplexing (as opposed to time-multiplexing) of traffic and pilot signals. The time-dispersivity of the channel destroys the orthogonality between the traffic signal and the pilot, and consequently the traffic signal appears as a new interfering signal for the channel estimation/beamforming algorithm. In order to avoid this effect, we propose techniques that exploit both the presence of the training sequence and the structure of the traffic signal in a semi-blind fashion.