A 5G DMRS-based Signal for Integrated Sensing and Communication System
Fuente:
arXiv
Gespeichert in:
| Hauptverfasser: | , , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2023
|
| Schlagworte: | |
| Online-Zugang: | |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866911787607130112 |
|---|---|
| author | Wei, Zhiqing Li, Fengyun Liu, Haotian Chen, Xu Wu, Huici Han, Kaifeng Feng, Zhiyong |
| author_facet | Wei, Zhiqing Li, Fengyun Liu, Haotian Chen, Xu Wu, Huici Han, Kaifeng Feng, Zhiyong |
| contents | Integrated sensing and communication (ISAC) is considered as the potential key technology of the future mobile communication systems. The signal design is fundamental for the ISAC system. The reference signals in mobile communication systems have good detection performance, which is worth further research. Existing studies applied the single reference signal to radar sensing. In this paper, a multiple reference signals collaborative sensing scheme is designed. Specifically, we jointly apply channel state information reference signal (CSI-RS), positioning reference signal (PRS) and demodulation reference signal (DMRS) in radar sensing, which improve the performance of radar sensing via obtaining continuous time-frequency resource mapping. Crámer-Rao lower bound (CRLB) of the joint reference signal for distance and velocity estimation is derived. The impacts of carrier frequency and subcarrier spacing on the performance of distance and velocity estimation are revealed. The results of simulation experiments show that compared with the single reference signal sensing scheme, the multiple reference signals collaborative sensing scheme effectively improves the sensing accuracy. Moreover, because of the discontinuous OFDM symbols, the accuracy of velocity estimation could be further improved via compressed sensing (CS). This paper has verified that multiple reference signals, instead of single reference signal, have much more superior performance on radar sensing, which is a practical and efficient approach in designing ISAC signal. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2312_02170 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | A 5G DMRS-based Signal for Integrated Sensing and Communication System Wei, Zhiqing Li, Fengyun Liu, Haotian Chen, Xu Wu, Huici Han, Kaifeng Feng, Zhiyong Information Theory Signal Processing Integrated sensing and communication (ISAC) is considered as the potential key technology of the future mobile communication systems. The signal design is fundamental for the ISAC system. The reference signals in mobile communication systems have good detection performance, which is worth further research. Existing studies applied the single reference signal to radar sensing. In this paper, a multiple reference signals collaborative sensing scheme is designed. Specifically, we jointly apply channel state information reference signal (CSI-RS), positioning reference signal (PRS) and demodulation reference signal (DMRS) in radar sensing, which improve the performance of radar sensing via obtaining continuous time-frequency resource mapping. Crámer-Rao lower bound (CRLB) of the joint reference signal for distance and velocity estimation is derived. The impacts of carrier frequency and subcarrier spacing on the performance of distance and velocity estimation are revealed. The results of simulation experiments show that compared with the single reference signal sensing scheme, the multiple reference signals collaborative sensing scheme effectively improves the sensing accuracy. Moreover, because of the discontinuous OFDM symbols, the accuracy of velocity estimation could be further improved via compressed sensing (CS). This paper has verified that multiple reference signals, instead of single reference signal, have much more superior performance on radar sensing, which is a practical and efficient approach in designing ISAC signal. |
| title | A 5G DMRS-based Signal for Integrated Sensing and Communication System |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2312.02170 |