Research On Orthogonal Time Frequency Space Modulation-based Waveform Technologies In Integrated Sensing And Communication

With the continuous evolution of emerging intelligent services and applications,the sixth-generation mobile communication system not only pursues higher quality communication but also seeks high-precision sensing.In order to realize the fusion of communication and sensing,Integrated Sensing and Communication(ISAC)is regarded as the key enabling technology,and its core problem is the integrated waveform.Considering the demand and compatibility of integrating sensing in communication systems,communication-centric integrated waveform becomes the necessary technical support.The main schemes include integrated waveforms based on Orthogonal Frequency Division Multiplexing(OFDM)and Orthogonal Time Frequency Space(OTFS).The former has problems such as high peak-to-average power ratio and low Doppler tolerance,which limit its application in fast-changing environments.The ISAC waveform based on OTFS is more suitable for high-dynamic and fast-changing scenarios due to its advantages of high communication rate,large sensing range,and insensitivity to Doppler.However,the ISAC waveform based on OTFS still faces problems such as severe multipath interference in complex environments and limited performance during signal processing.To address the above issues,this thesis proposes an ISAC signal processing scheme to significantly improve the sensing performance by studying the ISAC waveform technology based on OTFS.The main research content and contributions of this thesis are as follows:To address the performance limitation of OTFS-based sensing algorithms,this thesis first studies sensing algorithms based on OTFS and proposes a sensing signal processing scheme based on Minimum Mean Square Error(MMSE)and Orthogonal Matching Pursuit(OMP).The scheme uses the MMSE criterion to minimize the mean square error of sensing,accurately estimates the radar sensing channel,and obtains the sparse approximation element.According to the maximal correlation between the residual and the atomic signal in OMP,the sparse approximation element of the radar sensing channel is obtained by iteratively reducing the residual.Simulation results indicate that,compared with the existing research,the proposed scheme can not only accurately sense the target,but also improve the sensing performance without significantly increasing complexity.Second,in response to the issues of inter-symbol interference caused by multipath effect and the limited sensing accuracy under integer Doppler,the OTFS-ISAC with cyclic prefix(CP)under fractional Doppler is studied.This thesis proposes a signal processing scheme under fractional Doppler in CP-OTFS-based ISAC system.A pilot-assisted cross-correlation ISAC channel estimation algorithm is used to search for the matching fractional Doppler through the cross-correlation function of the pilot equivalent channel,so as to accurately realize the shared ISAC channel estimation.By proving the sparsity and block diagonal characteristics of the equivalent channel response matrix in time domain,the MMSE equalization algorithm based on time domain block is adopted.And the size of matrix inversion is reduced by block operation to reduce the complexity of time domain equalization.Simulation results show that the proposed scheme can still maintain reliable communication in mobile scenarios,and improve the accuracy of sensing under high SNR conditions.This article focuses on the research direction of OTFS-based ISAC waveform technology,and designs ISAC signal processing scheme to improve communication and sensing performance.Through simulation verification,the proposed scheme can significantly improve ISAC performance and meet the requirements of high-reliability communication and high-precision sensing in high dynamic ISAC scenarios.The study provides theoretical and technical support for applications.