As a key technology in OFDM, channel estimation directly affects the performance of OFDM systems. However, the existing least squares estimation (LS) algorithm and minimum mean square error estimation (MMSE) algorithm have their own shortcomings. Therefore, this paper proposes a new algorithm called average feedback (AF), which uses the correlation information between two adjacent OFDM symbols to average and feedback the estimation results of the LS algorithm to reduce the impact of Gaussian white noise and inter-channel interference (ICI) on the channel estimation results. The simulation proves that the new algorithm improves the performance of the LS algorithm, especially in low signal-to-noise ratio environments. 【Key words】 OFDM channel estimation least square(LS) average feedback (AF) 【Abstract】 Channel Estimation technique is one of the key techniques in OFDM and it directly affects the performance of the system. Some existing methods, such as LS method and MMSE method, having some obvious shortcomings respectively. So an improved method is proposed in this paper. The optimal method reduces the interfere of noise and ICI by using the related information between two adjacent OFDM symbols to feedback and average. At last, the simulation result demonstrates that, compare with original LS methods; new methods improve the BER performance, especially in the low SNR environment.【Key words】 OFDM channel estimation least square(LS) average feedback (AF)
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