Decision Feedback Channel Estimation Algorithm Guided By Training Sequence

Focusing on the future wireless mobile communication system, if we want to achieve high-speed, high quality and seamless coverage of the real-time tracking, it is necessary to introduce new technologies and new means. With the rapid development of wireless communication technology, spectrum shows the growing tension. How to save and rationaliy use the available spectrum resources is becoming an urgent problem to solve, so that people will pay more attention to the orthogonal frequency division multiplexing(OFDM, Orthogonal Frequency Division Multiplexing)technology. And the reason to employ OFDM lie in its high spectral efficiency and strong anti-multipath capability. Further research on the OFDM channel estimation is that only the timely access to channel state information is the way to demodulate the channel timely and accurately. This thesis that I present a further analysis on the estimation of OFDM technology provides a training sequence based on decision feedback guide channel estimation algorithm for channel estimation.Firstly, the paper briefly reviews background, significance and motivation of the OFDM technology research.Secondly, the paper analyzes the characteristics of several wireless channels and sets out the OFDM channel model for estimation and demonstrate the model detailedly.Thirdly, the paper describes the basic principles of OFDM systems and analyses the advantages and disadvantages for the OFDM system. This paper not only presents the key technologies of OFDM in detail, but also discusses the key technologies in the OFDM system channel estimation techniques. Further, the paper focuses more analyses on pilot symbols and interpolation estimation, blind channel estimation algorithm, semi-blind channel estimation method.Finally, I extend the analysis further to OFDM channel estimation techniques and focus on the time-varying channel basing on pilot and decision feedback channel estimation. In this paper, I introduce Least Square (LS) and Minimum Mean Square Error (MMSE) algorithms and relevant improved algorithms and a variety of interpolation algorithms. Because the channel time variation will lead the system to subcarrier orthogonality to be destroyed, this will inevitably produce a channel interference (ICI). Using the training sequence to guide the decision feedback channel estimation algorithm for channel estimation, the paper proposes the improved algorithm by employing the moving average the instantaneous value of channel estimation to optimize the original decision feedback algorithm. Simulation results show that: in the time-varying channel environment, the use of an improved decision feedback channel estimation algorithm reduces the error rate and minimum mean square error.