Research On Channel Estimation Technique For OFDM Based Mobile Communication Systems

With the development of science and technology,the field of mobile communication needs to provide higher speed,higher quality of voice and data services to meet the needs of the community.Orthogonal frequency division multiplexing(OFDM)technique has been widely used in the physical layer of the current 4G standard due to its high spectral efficiency,anti multipath delay and channel fading,it is also an alternative technology for future 5G standards.Channel estimation is one of the key technologies in OFDM wireless communication system,which directly affects the coherent detection,channel equalization and decoding in OFDM system.The specific research contents are as follows:Firstly,based on the research of DFT channel estimation,the improved algorithm is given.The improved algorithm uses the weight parameter to set the dynamic threshold,in which the weight parameter is obtained by the channel state information of LS.The threshold is related to the noise variance and the average signal to noise ratio.The improved algorithm can effectively reduce the influence of noise,so as to improve the performance of channel estimation,The performance is verified by simulation experiments.Secondly,in the research of sparse channel estimation,an improved scheme is proposed to reduce the computational complexity of the multipath matching pursuit algorithm.The improved algorithm adjusts the number of sub paths generated by the path according to the probability that the path is selected in each layer of the tree structure,and reduces the generation of paths with small selection probability.The performance of the improved algorithm is verified by simulation experiments.Finally,we study the pilot optimization problem in sparse channel estimation.The performance of the random search optimization algorithm is very dependent on the size of the sample size.In this paper,the corresponding improvement scheme is given.The improved algorithm expands the searching range by implementing parallel search strategy to the elements of specific location in all pilot index sets.The optimal pilot pattern is selected by using the new cross-correlation minimum criterion based on Euclidean distance.When compared to the random search algorithm,the improved algorithm has higher estimation accuracy.The performance of the improved algorithm is verified by simulation experiments.