Research On Time Delay Estimation Algorithms Oriented To Terminal Positioning In NB-IoT

The delay estimation algorithm is the basis of Observed Time Difference of Arrival positioning,and the accuracy of the delay estimation directly affects the accuracy of the position estimation.Narrow Band Internet of Thing(NB-IoT)is an emerging and widely used technology,and it has a high position in location-aware applications.Since NB-IoT has the characteristics of Low Power Wide Area technology and low sampling rate,the design of delay estimation algorithm should take into account the constraints on the power consumption and the cost of terminal equipment derived from them.Based on the NBIoT terminal positioning,this thesis studies the delay estimation algorithm.The specific research contents are as follows:1.Aiming at the characteristics of NB-IoT such as low power consumption,low cost and low sampling rate,a delay estimation algorithm based on inter-cell interference cancellation is proposed.On the one hand,in order to eliminate the influence of inter-cell interference signals,the proposed algorithm integrates the continuous interference cancellation algorithm into the entire time delay estimation process.On the other hand,in order to break through the restrictions of the sampling rate and improve the accuracy of time delay estimation,and then the idea of time-frequency cross-correlation overlapping based on traditional correlation algorithms is introduced.The idea mainly includes the following two stages: The first stage,the preliminary delay estimation value is obtained by using the correlation algorithm,and the first arrival path searching based on the noise threshold is used to suppress the influence of multipath effect;The second stage,part of received signals are interpolated to obtain the accurate estimation of time delay.Simulation results show that the proposed algorithm can significantly improve the delay estimation accuracy of NB-IoT.2.Aiming at the problem of low estimation accuracy and high computational complexity caused by low rate and low-power consumption of NB-IoT,a new time delay estimation algorithm based on sparse reconstruction with cost function model is proposed.Firstly,the traditional Orthogonal Matching Pursuit(OMP)algorithm and the narrowband positioning reference signal are used to predict the delay value,and then the redundant dictionary is constructed based on the pre-estimated delay value.Based on this,the improved OMP algorithm is used to further estimate the delay value.The idea of adding a cost function to the algorithm reduces the multidimensional delay estimation into multiple one-dimensional time delay estimation,and uses sparse reconstruction to eliminate the interference between signals.In addition,in order to eliminate the problem of local optimization caused by dimensionality reduction,the soft threshold is reasonably set to effectively and quickly terminate the iterative process of the cost function model.The simulation results show that compared with the traditional correlation algorithm,OMP algorithm and other delay estimation algorithms,the proposed algorithm has better detection performance and higher delay estimation accuracy.