Coprime-based Frame-Level Sensing OFDM Waveform for 5G NR Integrated Radar Sensing and Communication via Downlink Sensing

Xiaoye Wang1,2; Zhaocheng Yang3; Fan Liu2; Ping Chu3; Jian Zheng3

2024

10.1109/JSEN.2024.3416377

IEEE Sensors Journal   影响因子和分区

2379-9153

In 5G new radio (NR) integrated sensing and communication (ISAC) systems, the overhead of sensing time resources in waveform design is a key metric. Traditional uniform pulse sensing waveforms, which require fixed time slot positions, incur large sensing overhead and may not be feasible within the context of existing 5G NR standards for low-latency scenarios. To address this issue, two novel frame-level sensing waveform designs based on double coprime sampling structures are proposed via downlink sensing. Specifically, two types of novel orthogonal frequency-division multiplexing (OFDM) structure pulse sensing waveforms based on coprime sampling are first proposed to accommodate the specific 5G NR frame structure. Then, a low-complexity frequency-domain radar signal processing method is proposed for sensing target detection and velocity estimation based on the constructed equivalent virtual fast-slow-time domain signal. Moreover, the theoretical sensing performance of the proposed waveforms and the computational complexity of the sensing method are thoroughly analyzed. Compared with the conventional uniform OFDM-based waveform design, the proposed coprime-based frame-level OFDM sensing waveforms utilize significantly fewer time slots, resulting in reduced sensing overhead with slight sensing performance loss. Numerical examples are presented to illustrate that the proposed waveforms can offer robust sensing performance with reduced sensing overhead and have a computational complexity a little higher than that of conventional fast Fourier transform algorithms.

EI

其他

ENGINEERING

1.College of Computer Science and Engineering, Huizhou University, Huizhou, China
2.School of System Design and Intelligent Manufacturing, Southern University of Science and Technology, Shenzhen, China
3.College of Electronics and Information Engineering, Guangdong Key Laboratory of Intelligent Information Processing, Shenzhen University, Shenzhen, China

Xiaoye Wang,Zhaocheng Yang,Fan Liu,et al. Coprime-based Frame-Level Sensing OFDM Waveform for 5G NR Integrated Radar Sensing and Communication via Downlink Sensing[J]. IEEE Sensors Journal,2024,PP(99).

Xiaoye Wang,Zhaocheng Yang,Fan Liu,Ping Chu,&Jian Zheng.(2024).Coprime-based Frame-Level Sensing OFDM Waveform for 5G NR Integrated Radar Sensing and Communication via Downlink Sensing.IEEE Sensors Journal,PP(99).

Xiaoye Wang,et al."Coprime-based Frame-Level Sensing OFDM Waveform for 5G NR Integrated Radar Sensing and Communication via Downlink Sensing".IEEE Sensors Journal PP.99(2024).