Research On Synchronization And Channel Estimation Based On Sparse Signal

Sparse Representation has a lot of use cases in different areas.The most important application in signal processing is to extract important elements from a large number of clutter signals with different requirements.The sparse representation theory employs a more efficient sampling rate to measure the original sample by abandoning the pristine measurements of Shannon's sampling theorm(SST)and Nyquist sampling law(NSL).And then adopts an optimal reconstruction algorithm to reconstruct the sample.In the context of compression sensing,it is assumed that all the signals are sparse or approximately sparse enough.Compared with the primary signal space,the size of the set of possible signals can be decreased largely under the constraint of sparsity.Therefore,a large number of algorithms based on sparse representation can effectively solve the problem of signal reconstruction and recovery in signal processing.And sparse representation technology can save a lot of sampling time and sampling storage,which has great advantages and potential.The Global Positioning System(GPS)synchronization process is to get the propagation time that the signal from the positioner to the positioning satellite.At present,the synchronization algorithm is relatively mature,but how to carry on the more simple and effective synchronization process is still a researchable direction,especially it is getting more popular in all kinds of intelligent home and micro-device with positioning function.Channel estimation technology has always been one of the important research directions in the field of communication.Nowadays,the research of channel estimation under multiple antennas system is one of the hotspots in the trend of the fifth generation communications research.In this paper,the fast GPS synchronization method based on sparse Fourier transform and the channel estimation technique under multi-antenna system are studied from the sparse representation of the signal.In Chapter 1,The background and the research status of GPS synchronization technology and sparse channel estimation are summarized.Chapter 2 mainly studies the modeling analysis of the minimization problem for sparse representation.The paper introduces the different norm,analyzes the relationship between them,and then introduces the sparse reconstruction algorithm based on the greedy strategy for the solution of the paradigm minimization problem.In Chapter 3,the synchronization process of GPS synchronization is described,and the synchronization model is established.The sparse Fourier transform is also described in detail.For the sparse Fourier transform using the aliasing operation to reduce the Fourier transform scale of the process of revelation,we can borrow it to the GPS synchronization process and reduce the scale of FFT and inverse Fourier transform(IFFT)operation,which can achieve the purpose of reducing the complexity of the entire synchronization process.The simulation results also show that the synchronization time complexity of fast GPS is much smaller than that of traditional FFT-based synchronization algorithm,and has the practical application prospect.In Chapter 4,the channel estimation technique of multi-antenna is studied.Firstly,the multi-antenna channel is analyzed,and the sparsity characteristics of the tap in the time domain channel impulse response are described.In this case,a preamble sequence with good correlation and the pilot in the OFDM block are given in the OFDM system in the case of the good correlation between the antennas in the multi-antenna system Design scheme.The estimation strategy of sparse reconstruction algorithm in OFDM is used to reduce the use of the pilot.At last part the channel estimation of the multi-antenna system is carried out by using the phase rotation pilot.The staggered shift operation of the important tap of the time domain channel is performed for the channel correlation of the associated transmit antenna,two important tap classification algorithms are designed and simulated with known shift factors.Conclusions of the work in the thesis are given in Chapter 5,At the same time,it points out the research points and research directions that the fast synchronization technology and the related antenna channel estimation still need to be carried out.