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Channel Estimation in Correlated Multi-Antenna OFDM Systems

서울대학교 대학원
Publication Date
  • Mimo-Ofdm 시스템
  • Mimo-Ofdm System
  • 안테나 상관
  • Antenna Correlation
  • 채널 추정
  • Channel Estimation
  • 직교 변환
  • Orthogonal Transform
  • Communication
  • Design


Orthogonal frequency division multiplexing (OFDM) can provide bandwidth efficiency and robustness to inter-symbol interference (ISI) with the aid of channel state information (CSI). It can obtain accurate CSI with the aid of pilot signaling in a packet-based communication system. Conventional schemes estimate the CSI by means of least-square (LS) method using received pilot signal. Then, the CSI corresponding to data transmission can be obtained by interpolating the CSI estimated from the received pilot signal in the time and frequency domain. Channel correlation property can be exploited by means of minimum mean squared error (MMSE) interpolation. However, MMSE methods may not provide desired performance when the channel is not sufficiently correlated in the time or frequency domain. In this dissertation, we exploit the correlation properties in the spatial domain as well as in the time and frequency domain. We consider the use of an MMSE channel estimation scheme in three dimensions; in the time, frequency and spatial domain. We analyze the MSE performance of the proposed 3-D MMSE channel estimation scheme in a numerical way and verify it by computer simulations. Pilot signal is often predetermined independently of the channel condition. We also consider adaptive pilot signaling to minimize the MSE according to the channel condition. The use of DFT-based channel estimation schemes is attractive in OFDM systems because it can easily be implemented using a fast Fourier transform (FFT) module implemented for OFDM. However, most of conventional DFT-based channel estimation schemes have been developed without exploitation of channel correlation in the spatial domain. We design a channel estimation scheme for MIMO-OFDM systems by means of transformation in the frequency and spatial domain. The CSI components whose power is less than a threshold are discarded to reduce the noise effect. Finally, the truncated CSI is inverse-transformed i

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