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In order to solve the problems of the conventional channel estimation method is not ideal in the performance of sparse channel estimation£¬Many algorithms do not take into account the pilot placement¡£The compressed sensing theory is applied to sparse channel estimation was investigated¡£After the analysis of  pilot pattern design criteria based on the CS theory measurement matrix cross-correlation minimization£¬A method was presented to the channel estimation mean square error criterion to select the CS algorithm£¬The OFDM system model  and the pilot programs  was established¡£The simulation results show that£ºThe pilot design for discrete stochastic approximation schemes for improvement£¬than the ergodicity search converges faster and more efficiently£¬the based on OMP algorithm  of channel estimation performance  is higher¡£

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In order to solve the problems caused by conventional channel estimation method which is not ideal in the performance of sparse channel estimation£¬many algorithms do not take into account the pilot placement. The compressed sensing theory applied to sparse channel estimation was investigated. After the analysis of  pilot pattern design criteria based on the CS theory measurement matrix cross-correlation minimization£¬a method was presented to the channel estimation mean square error criterion to select the CS algorithm£¬The OFDM system model  and the pilot programs  was established. The simulation results show that the modified pilot design for discrete stochastic approximation schemes is faster and more efficiently than the ergodicity search converges. Simultaneously, the channel estimation performance based on OMP algorithm is improved.

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