Research On Channel Estimation Of OFDM Technique Based On Compressed Sensing

Orthogonal Frequency Division Multiplexing(OFDM)technology has been widely used in mobile communication due to its high spectrum utilization,anti-frequency selective fading and anti-waveform interference.The wireless channel estimation plays an important role in the coherent detection,channel equalization and decoding of the OFDM system,and is one of the key technologies of the OFDM wireless communication system.In this paper,the OFDM channel estimation technology based on compressed sensing is deeply studied.The specific research contents are as follows:Firstly,in the study of channel estimation with known sparsity,an improved algorithm for reducing the computational complexity of multipath matching pursuit algorithm is proposed.The improved algorithm adjusts the sub-path size generated in the next iteration by setting a double threshold,and adjusts the probability of the selected path according to the cross-correlation size in each layer of the tree structure,thereby reducing the generation of poor performance paths and reducing the complexity of the algorithm.Secondly,in the study of channel estimation with unknown sparsity,a multi-path matching pursuit algorithm with unknown sparsity is proposed for the problem of low channel estimation accuracy and poor anti-noise robustness of stochastic gradient pursuit algorithm.In each iteration of the loop,the algorithm uses stochastic gradient pursuit instead of least square to improve the estimation accuracy,and further reduces the algorithm complexity by setting double thresholds and adjusting the selected path probability.Finally,the pilot optimization problem of channel estimation based on compressed sensing is deeply studied.An improved algorithm is proposed for the problem of channel estimation performance of the random search optimization algorithm is very dependent on the size of the sample size and the uncertainty of random selection.The improved scheme expands the search range by performing parallel double-loop search on the generated pilot index set,and then selects the optimal pilot pattern by using the new cross-correlation minimum criterion of the Euclidean distance,so that the optimal pilot search is operable and channel estimation accuracy is improved.The performance of the above three algorithms has been verified by simulation experiments.