Research On Mmwave Automotive Integrated Radar And Communication Technology Based On OTFS Modulation

In recent years,with the rapid increase of vehicles,improving safe driving coefficient has become the focus of various countries and car manufactures.Owing to the improvement of global science and technology and chip manufacturing capabilities,a large number of new safety technologies can be applied in practice,in which intelligent transportation system(ITS)is an effective way to solve automobile safety problems.ITS integrates information and communication technology and sensor technology into the infrastructure and vehicles of the transportation system,which greatly alleviates traffic congestion and improves the overall system safety.The key to ensuring the reliable and stable operation of ITS is to integrate the radar and communication system,and make full use of system hardware and spectrum resources,so as to facilitate the installation on the automobile platform.In view of the fact that the car is always in a high-speed moving scenario,the orthogonal time frequency space(OTFS)modulation signal which is inherently robust to the Doppler shift will be used as the integrated signal of joint radar and communication system in this thesis,and the millimeter-wave band,which is commonly used in the automotive radar,is selected as the carrier frequency.As for the OTFS-based millimeter-wave automotive integrated radar and communication system,some researches are conducted as follows:(1)Aiming at the problem of the vague system structure and parameter design in the existing OTFS-based automotive integrated radar and communication system,a set of parameters that meet the requirements of radar and communication systems at the same time are designed.In addition,a simple frame structure is utilized to avoid the mutual interference between the radar echo and communication signal.Regarding the poor peak-to-average power ratio(PAPR)performance of OTFS signal when the number of transmitted symbols is large,a PAPR reduction algorithm based on symbol precoding is proposed.Through an appropriate constraint,this algorithm can reduce the influence of the precoding matrix on the communication performance.Moreover,with the use of the block coordinate descent method,the complexity of solving the optimal precoding matrix can be reduced.(2)For the high time and space complexity of the existing delay-Doppler domain matched fil-ter algorithm,a low-complexity parameter estimation algorithm based on sparse Bayesian learning(SBL)is proposed.The algorithm firstly takes advantage of some prior information,such as target motion parameter limits,and sparse structure of the radar channel to greatly simplify the radar tar-get signal estimation model,and then the sparse signal estimation model is obtained.On the basis of conventional SBL algorithm,two-dimensional pattern-coupled structure and generalized approximate message passing(GAMP)approach are combined to significantly reduce the computational complex-ity of the algorithm.Furthermore,it also can achieve a higher peak-to-sidelobe ratio(PSLR),which is helpful to reduce the mutual interference in the multiple targets scenarios.(3)With respect to high complexity caused by nonlinear demodulation in the existing message passing(MP)algorithm,two low-complexity linear demodulation algorithms are proposed,both of which have their own advantages.Since the block LDL decomposition based transformed domain minimum mean squared error(MMSE)algorithm does not require iterative calculations,it can sig-nificantly reduce the amount of calculation when the Doppler shift is small.However,this algorithm is merely a simple linear estimation,thus its performance on bit error rate(BER)is still inferior to MP algorithm,and the communication rate of the system needs to be slower when the Doppler shift is large.For the transformed domain maximal ratio combining(MRC)algorithm,it not only can exploit the diversity gain of the path to improve the signal-to-noise ratio(SNR)of symbol detection,but also use the sparse structure of the effective channel matrix in the transformed domain to reduce the com-putational complexity.Consequently,the performance of this algorithm is better than MP algorithm in terms of BER and complexity.