Research On Doppler Shift And Channel Parameter Estimation And Spectrum Sensing For LEO Satellite Communications

In low earth orbit(LEO)satellite communication,there are many kinds of interference such as Doppler frequency shift and multipath fading in the channel,which seriously affect the receiving performance,at the same time the primary user in the actual communication takes up only a small bandwidth,Sparse characteristics in the frequency domain,the spectrum utilization is low.Aiming at these problems,this thesis mainly studies the spectrum sensing and sparse channel estimation of LEO satellite,which can accurately sensing the spectrum and estimate the channel state information,so as to improve the spectrum utilization and transmission efficiency of the channel.Firstly,the background,current situation and development trend of LEO satellite communication are introduced.Secondly,established a typical Doppler frequency shift model of the LEO satellite channel,and analyzed its characteristics.After that,for single LEO satellite spectrum resources are limited,mainly studies used of the compressed sensing and cognitive radio technology to achieve sparse spectrum sensing and channel estimation.Finally,summarize the whole text,Namely for the satellite channel have high Doppler frequency shift and sparsity,improved the traditional Doppler shift estimation algorithm and uses the compressed sensing reconstruction algorithm to realize the spectrum sensing and channel estimation of the satellite channel.Improve the channel communication transmission anti-jamming performance.The full text of the content and innovation are as follows:1.Aiming at the characteristics of low and medium elliptical orbit satellite channel,a new algorithm is proposed,which uses the parameters of semi-major axis,eccentricity and carrier frequency to predict the Doppler shift of satellite.The algorithm respectively in the Doppler frequency shift formula derivation and theoretical analysis and obtained the analytical solution of the estimated value,which can be used as pre-compensation of Doppler frequency shift to assist channel estimation.The simulation results show that the proposed algorithm can accurately calculate the Doppler shift parameters of different satellite orbits,and compared with traditional 3D coordinate algorithm,the complexity is reduced and improved efficiency;2.The traditional inserting pilot channel estimation algorithm reduces the channel utilization due to the pilot occupying additional channel bandwidth.So used of compression sensing reconstruction algorithm,proposed an improved OMP fast sparse channel estimation algorithm.The algorithm is based on the OMP algorithm,by using the multi-atom selection method at each iteration,that is to select the optimal M column vector in the residuals and the measurement matrixinner product to calculate a corresponding estimate.Finally,optimize all estimates,Select K maximum value to form an optimal estimate vector h.Under the same estimation,the improved OMP algorithm pilot is much less than the traditional LS algorithm,thus saving more bandwidth.The simulation results show that the improved algorithm is more time consuming than the LS algorithm when the training sequence length is the same,but it can obtain more excellent channel estimation performance;3.Aiming at the limitation of single satellite communication spectrum resource in LEO constellation,use of cognitive radio collaborative wideband spectrum sensing algorithm,to realize the accurate sensing of the wideband spectrum.According to the Joint Sparse Model(JSM-2),a fast and low complexity spectrum sensing algorithm is proposed.Its based on the distributed compression sensing orthogonal matching pursuit algorithm(DCS-OMP),the former time perception result as a priori condition,to sensing the current time spectrum occupancy.And in the signal reconstruction,the residual threshold as the decision condition,which greatly reduces the number of iterations and simplifies the reconstruction complexity.The simulation results show that when the spectrum occupancy is change slow,Compared with the DCS-OMP algorithm,the proposed algorithm achieves similar performance,also can reduce the complexity and delay significantly when the number of cognitive users is large.When the sparsity is 20,the signal length is 500,and the SNR is 15 dB,the proposed algorithm reduce 0.2032 of the reconstructed spectrum error and 13.8% of the time consumed compared with the DCS-OMP algorithm;In this article,aiming at the problems of Doppler frequency shift,multipath fading and lower channel spectrum utilization of LEO satellite channel,proposed a fast estimation algorithm of Doppler frequency shift and the sparse channel estimation and spectrum sensing algorithm of LEO satellite based on compression sensing.The proposed algorithm is helpful to the efficient identification,estimation and effective utilization of LEO satellite channel,and it will be widely used in the future,such as high speed satellite multimedia communication and broadcasting.