Kalman filter based channel estimation method in wireless communication and its performance optimization

In this paper, with the help of the real-time state observation property of the Kalman ilter method, we propose to use the Kalman ilter method for channel estimation of OFDM wireless communication system.The linear interpolation method is used to deal with the fading process of data symbol positions, and the Kalman ilter estimation expression of the fading process is obtained.And considering the computational complexity of the channel estimation algorithm, the channel estimation is optimized by adding the 1st order AR model into the channel model.The Doppler frequency is used as the simulation parameter to analyze the operational performance of the Kalman ilter channel estimation method under different Doppler frequencies.To further broaden the applicability of the proposed method in this paper, a MIMO-OFDM system is introduced, and numerical simulations are conducted to analyze the relationship curves between the outage probability and the SNR performance under the OFDM channel processing module for both the random channel and the random channel with OFDM modulation.In the massive MIMO multipath random transmission channel, the better the SNR performance of the channel, the smaller the probability of generating interruptions.Meanwhile, in the presence of the same non-ideal factors (hardware impairments, interference noise) interruption probability impairments of the channel, the SNR in OFDM-ideal state is about 10 dB more than the OFDM-hardware impairments simulation value.