Modern Wireless Mobile Communication System, Channel Estimation Algorithm

In wireless mobile communications, the delay dispersion and the limitation of channel bandwidth may cause intersymbol interference (ISI) and thus the channel is frequency selective. The relative motion between the base station and the mobile results in random frequency modulation and the channel becomes time selective. Generally the channel is both frequency selective and time selective. In order to achieve reliable communication, the receiver must estimate and equalize the channel to combat the distortions introduced by the channel. In this dissertation, the estimation algorithms of time-varying frequency selective channel in modern wireless communication systems including WCDMA uplink, WCDMA downlink with space time transmit diversity and MIMO system are investigated. The main researching work in this dissertation can be summarized as follows: Some estimation methods of time-varying frequency selective channel are deeply studied in WCDMA uplink system. The algorithms of one slot averaging, weighted multi-slot averaging (WMSA) and interpolation are analyzed and compared. The idea of decision-feedback is also applied in the channel estimation method and better performance is achieved. The case when the receiver uses antenna array is also introduced simply. The space-time transmit diversity (STTD) architecture in WCDMA downlink is analyzed and the channel estimation method based on the Common Pilot Channel(CPICH) is investigated. Because there is no power control in CPICH, the received common pilot signal power is possibly very low if the mobile is far from the base station, and this time the channel estimates is inaccurate. A method of combining CPICH and the pilot symbols in Dedicated Physical Control Channel (DPCCH) is investigated to combat this shortcoming. The problem of time-varying frequency selective channel estimation and equalization in multi-input multi-output (MIMO) system is studied. Kalman filter is used to track the channel variation and the Minimum Mean Square Error Decision Feedback Equalizer (MMSE-DFE) to equalize the channel. Polynomial fitting is used to bridge the gap between the channel estimates produced by the Kalman filter and those needed for the DFE decision. The computer simulations are performed for the algorithms investigated in this dissertation and the performance comparison is legible.