Research On Pilot-assisted Channel Estimation In OFDM System

Orthogonal frequency division multiplexing (OFDM) technology as a high spectrum efficiency can be effective against frequency selective fading and time dispersion, etc., can provide high-speed and high-quality communication services, it is more and more attentions have been become a key fourth-generation mobile communication technology and current international research in the field of wireless communication hot spots. Wireless channel has a very important impact of the wireless communication system performance, and channel estimation is the basis for coherent detection, demodulation and balanced, therefore channel estimation has an important impact on performance of the OFDM system, and it has considerable research value.This paper mainly studies the pilot assisted channel estimation, and summarizes the statistical properties of the general wireless channel multipath channel characteristics and basic principle of OFDM, especially multipath fading and Doppler shift of the impact on system performance, an extensive overview of channel estimation techniques such as least squares (LS), minimum mean square error (MMSE) and interpolation algorithm based on pilot employed in OFDM systems are presented, and analyzes the advantages and disadvantages of the various algorithms.LS algorithm based on the channel estimate when the impact of the neglect of the noise, making estimation difficult to obtain good estimation performance. To solve this problem, we propose an improved-scaled least squares (ILS) algorithm. The algorithm introduces a scale factor, the factor is derived based on a kind of a smaller channel estimation mean square error (MSE) of the LS algorithm, and the algorithm takes into account the impact of the noise variance on the performance and solves the drawbacks of difficult to obtain the channel correlation matrix by using the LS algorithm. To further improve the performance of LS algorithm, we propose an a scale factor and shifted matrix based on the least squares (SSLS) algorithm, the shifted matrix is derived based on a kind of a smaller channel estimation MSE of the LS algorithm, and the algorithm solves the drawbacks of difficult to obtain the channel correlation matrix by using the LS algorithm. Simulation results demonstrate the effectiveness of the proposed algorithm.MMSE channel estimation algorithm for the need to use the channel correlation matrix, and prior information difficult to obtain in the practical application of the drawbacks, we propose a robust minimum mean square error (RMMSE) algorithm. The algorithm assumes that the channel correlation matrix is a unit matrix, and making MMSE algorithm have certainly robustness, at the same time getting a sub-optimal estimator. The algorithm solves the drawbacks of difficult to obtain the channel correlation matrix by using the LS algorithm and the sub-optimal estimator. Simulation results demonstrate the effectiveness of the proposed algorithm.