Improved Maximum Doppler Frequency Shift Estimation Method And Its Application

The feature parameter extraction of channel is the basis of obtaining channel state and ensuring the quality of wireless communication.At the same time,with the increasing number of users,spectrum resources are becoming increasingly tense,and channel feature parameter extraction is the key to the rational allocation of communication resources.The maximum Doppler frequency shift is a small-scale characteristic parameter of the wireless channel,which is the main indicator reflecting moving speed of the terminal and channel fading degree.It plays an active role in the resource management and handover of the communication system.Therefore,it is of great significance to extract the maximum Doppler frequency shift parameter of wireless channel.The dessertation studies theories and applications of maximum Doppler frequency shift estimation in Rayleigh channel and single input multiple output(SIMO)channel.The main research work is as follows:(1)Aiming at solving the problems of existing maximum Doppler frequency shift estimated method in noisy environment which have poor estimation accuracy and high resource consumption,an improved method of noise matching based on singular entropy incremental curvature is proposed.First,we decompose the matrix of received signal envelope with noise by singular value,and find the maximum value of singular entropy incremental curvature to ensure that the useful component of signal is not damaged.Then,the appropriate matrix reconstruction order can be selected according to optimal filter bandwidth ratio.Last,we can estimate the maximum Doppler frequency shift by the envelope of reconstructed signal.(2)Due to existing a small numbers of Rician channels in SIMO system which lead the application of level crossing rate algorithm to appear deviation of statistical results,a method of deviation value elimination based on channel discrimination is proposed.First,we use the probability density function of envelope to distinguish the types of each sub-channel.Then,the maximum Doppler frequency shift of each sub-channel can be calculated according to the results of discrimination.Last,we construct a table of one-way ANOVA,and eliminate the deviation value of estimated results through variance analysis to get the effective statistical results of the maximum Doppler frequency shift.The experimental results show that the proposed method one can improve theefficiency of algorithm and reduce the time cost of algorithm without repeated low-pass filtering of received signal envelope in noisy environment,and ensure the accuracy of the maximum Doppler frequency shift.The proposed method two realizes the applicability of level crossing rate algorithm at the system level,and expands the application range of algorithm,and ensures that the estimation result is not affected by the Rician factor of each sub-channel,and improves the estimation accuracy.