Joint Estimation Of MIMO-OFDM Channel And Its Correlation

MIMO technology can be used to improve the system capacity and spectral efficiency significantly without increasing bandwidth. Meanwhile, OFDM technology is attracting more and more attention for its high tolerance to multipath fading. M1M0-0FDM technique, widely regarded as a most promising scheme, is efficient in wideband multimedia transmission because of its good ability in anti fading, high channel capacity and high data rate. In order to improve the system performance, many aspects of research, such as synchronization, equalization, coding, multiuser interference suppression etc have attracted great attention. The research of channel estimation, as one of the most important aspects in mobile communication, has achieved its significant status in signal resume, transmitter-receiver strategy and resource allocation. At present, most research of estimation of MIMO-OFDM channel are based on the supposition that the channel is under the identical independent distribution. Using MMSE (Minimum Mean Square Error) arithmetic taking the place of LS (Least Square) arithmetic, better performance will be obtained when CCI (Channel Correlation Information) is known. However, the CCI is unknown and difficult to get in practical environment. Furthermore, CCI is indeed in need in some other fields, such as antenna selection, adaptive modulation, adaptive power allocation and so on. Based on the above analysis, this dissertation undertakes some research work on channel estimation and channel correlation estimation in the MIMO-OFDM system.By lucubrating in the statistic characteristic of wireless fading channel and the principle of MIMO-OFDM, we propose two methods to estimate the channel and its correlation. In the first method, we estimate MIMO channel and channel correlation by using the fourth order cumulant Without pilot. This method can save bandwidth. The shortage is that the computation is too complicated. In the second method, we use the wavelet decomposition to eliminate the noise portion from the correlation matrix of the received signal, and then calculate the channel correlation. Finally, we utilize MMSE rule to estimate the channel response. From the theoretic analysis and result of simulation, we can conclude that the method is not only simple but also exact.