Joint Channel Estimation and Maximum Likelihood Data Detection using Kalman Filter for OFDM system in Time-Variant Channels

• Main Authors: Chen, Yu-Wei, 陳又維
• Other Authors: Tsai, Yuh-Ren
• Format: Others
• Language: en_US
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/71556539094353407117

碩士 === 國立清華大學 === 通訊工程研究所 === 97 === For orthogonal frequency division multiplexing (OFDM) systems in wireless mobile application, the orthogonality between subcarriers is very important. Nevertheless, user mobility induce a time-varying channel, it will destroy the orthogonality between subcarriers and caused intercarrier interference (ICI), degrades data detection performance. To enhance the performance of OFDM systems in a time-varying channel, we use Kalman filter and Maximum-Likelihood data detection algorithm to detect data symbol. We use Kalman filter to track channel variation between subcarriers in frequency domain within an OFDM symbol period while lots of study focus on using the time correlation in channel variation instead of frequency correlation. Although the statistic method of finding channel correlation coefficients failed, we find an optimal coefficient for our scheme. Simulation results show that our method works well in high Doppler scenario. This is very important for the service provider that needs to service the user that moving very fast.