Research On Channel Estimation Technique Based On Pilots For MIMO-OFDM Systems

With the rapidly development of wireless communication technique and growing requirement about high-speed multimedia data services, how to develop system capacity and improve the efficiency of bandwidth becomes the key questions of wireless communication technique. MIMO-OFDM system which can greatly improve communication capacity and band efficiency has been considered as the core technique of future wireless transmission. Channel estimation technique is regarded as a key technology for channel information is required in MIMO-OFDM systems for combination diversity, coherent demodulation and space-time decoding. In this paper, the channel estimation technique in MIMO-OFDM systems is investigated, and put the emphasis on pilot-based channel estimation methods. Then two improved algorithms are given respectively based on the mode of pilot and FFT algorithm.First, the background and development of OFDM and MIMO technologies are introduced. The characteristic of communication channel models, the principle of OFDM, MIMO, MIMO-OFDM system and the space-time coding in MIMO system are also discussed. Then the channel capacity and the space-time coding are analyzed based on MATLAB simulation.Second, the channel estimation techniques for SISO-OFDM systems are investigated. The mode of pilot are studied, and the performance of LS algorithm and LMMSE algorithm is compared and analyzed, then some interpolation algorithms are discussed. A pilot converse of the adaptive channel estimation technology is researched, and the improved scheme has better performance than the basic algorithm and it can also improve the spectrum efficiency compared with the block-type pilot algorithm. Finally, the channel estimation techniques for MIMO-OFDM systems are investigated based on the channel estimation techniques for OFDM systems. The design of pilot-pattern is studied. Then we propose an improved pilots filtering compare-FFT algorithm based on the FFT algorithm. The simulation results show that the proposed algorithm has better performance.