Semi-blind Channel Estimation For MIMO-OFDM Communication Systems

Since the1960s, the development and applications of wireless communication technologieshad brought people a lot of communication services, such as smooth voice, clear data transmissionand video. In the development of next generation wireless communication, it will face manyproblems like limited system spectrum resource and complex transmission environment. In a largenumber of new technologies, multiple-input multiple-output (MIMO) technology using multipleantennas both in transmitter and receiver, it provides space multiplexing gain and spatial diversitygain for wireless communication systems, this will not only exploit spatial resources and improvespectral efficiency, but also can overcome the multipath effects which caused by wireless channel.Orthogonal frequency division multiplexing (OFDM) technology has advantage in high spectrumefficiency, it can against frequency-selective fading and overcome inter symbol interference (ISI)which caused by frequency-selective wireless channel effectively. Therefore, multiple-inputmultiple-output orthogonal frequency division multiplexing (MIMO-OFDM) wirelesscommunication system gains a more widespread concern, because it has high spectrum efficiency,strong anti-interference ability and easy to implement.However, MIMO-OFDM wireless communication systems are usually sensitive withfrequency offset of carrier and phase noise. The multipath delay and Doppler frequency shift andother properties of wireless channel will cause inter carrier interference (ICI). In order to getOFDM signal accurately in the receiver and do coherent detection, channel estimation isindispensable. In this paper, MIMO-OFDM communication system channel estimation is the maintopic, the main purpose is to improve the channel estimation performance. The research and workcan be summarized as follows:1. Compare and analysis different pilot-based non-blind channel estimation for MIMO-OFDM communication system, such as the Least Square(LS) algorithm, the Minimum MeanSquare error(MMSE) algorithm and the Singular Value Decomposition (SVD) algorithm. Thereare some conclusions: The MMSE estimation algorithm is more effective than the LS estimationalgorithm and SVD estimation algorithm, the SVD estimation algorithm is better than the LSestimation algorithm.2. Focus on the research of the subspace semi-blind channel estimation methods for MIMO-OFDM communication system, in the creative process, this paper not only describes the basictheory, but also selects an iterative algorithm to improve the existing problems and designs simulation experiments, finally learned that the improved algorithm can not only maintain theadvantages of semi-blind channel estimation, but also improve the performance of the originalestimation algorithm.3. Studied QR decomposition based semi-blind channel estimation methods for MIMO-OFDM communication system. The paper firstly discusses the produce of QR decompositionbased channel estimation method and gives some conditions, then combines with blind estimationand training sequence based non-blind estimation method to analyze the effectiveness of this semi-blind channel estimation. The simulation results show this method can reduce the computationalcomplexity and improve performances.