Full 2D optimized window coefficients for improved range velocity estimation in 5G joint communication and sensing

被引:1
作者
Hofstadler, Michael [1 ,2 ]
Feger, Reinhard [1 ]
Stelzer, Andreas [1 ]
Lindorfer, Guenther [1 ,2 ]
Meingassner, Andreas [1 ,2 ]
Springer, Andreas [1 ,2 ]
机构
[1] Johannes Kepler Univ Linz, Inst Commun Engn & RF Syst, Linz, Austria
[2] Johannes Kepler Univ Linz, Christian Doppler Lab Digitally Assisted RF Transc, Linz, Austria
关键词
5G; joint communication and sensing; mmWave; New Radio; OFDM; RADAR; range estimation; sidelobe reduction; sounding reference signal; velocity estimation; DESIGN; RADAR;
D O I
10.1017/S1759078724001119
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This work presents an approach for optimization of window coefficients for 5G user equipment side sensing, using orthogonal frequency division multiplexing radar-based range and velocity estimation, based on the sounding reference signal (SRS) from the 5G New Radio (NR) standard. The signal configuration and the corresponding waveform are generated in compliance with the 3rd Generation Partnership Project (3GPP) standard for 5G. The limitations of conventional signal processing for resources available for sensing with the SRS are highlighted. The proposed approach, which optimizes the window coefficients to improve the sensing capabilities, is implemented through two methods. The first method employs a decoupled optimization strategy for range and velocity, showing high computational efficiency. Our results demonstrate that this method significantly improves the peak sidelobe level (PSL) of the velocity profile by over 15 dB, although it does not address the issue of diagonally located sidelobes, which occur due to non-uniform resource distribution. The second method adopts a comprehensive full 2D optimization technique. While it requires more computational resources and does not improve the PSL beyond the first method's achievements, it mitigates the diagonally located sidelobes issue. The level of these have been improved by more than 3 dB.
引用
收藏
页码:357 / 364
页数:8
相关论文
共 15 条
[1]  
3GPP, 2022, Technical Specification (TS) 23.502
[2]  
Boyd S., 2004, Convex Optimization
[3]  
Braun KM., 2014, THESIS KARLSRUHER I
[4]  
Diamond S, 2016, J MACH LEARN RES, V17
[5]   Low-Complexity Beamformer Design for Joint Radar and Communications Systems [J].
Dong, Fuwang ;
Wang, Wei ;
Hu, Ziying ;
Hui, Tong .
IEEE COMMUNICATIONS LETTERS, 2021, 25 (01) :259-263
[6]   Combining MIMO radar with OFDM communications [J].
Donnet, B. J. ;
Longstaff, I. D. .
2006 EUROPEAN RADAR CONFERENCE, 2006, :37-+
[7]  
HENDERSON HV, 1981, LINEAR MULTILINEAR A, V9, P271, DOI DOI 10.1080/03081088108817379
[8]  
Hofstadler M, 2023, 2023 20TH EUROPEAN RADAR CONFERENCE, EURAD, P335, DOI 10.23919/EuRAD58043.2023.10289464
[9]  
Hughes PK, 2000, 2000 IEEE INTERNATIONAL CONFERENCE ON PHASED ARRAY SYSTEMS AND TECHNOLOGY, PROCEEDINGS, P21, DOI 10.1109/PAST.2000.858893
[10]   Peak Sidelobe Level Based Waveform Optimization for OFDM Joint Radar-Communications [J].
Keskin, Musa Furkan ;
Tigrek, R. Firat ;
Aydogdu, Canan ;
Lampel, Franz ;
Wymeersch, Henk ;
Alvarado, Alex ;
Willems, Frans M. J. .
EURAD 2020 THE 17TH EUROPEAN RADAR CONFERENCE, 2021, :1-4