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A 5G DMRS-based Signal for Integrated Sensing and Communication System

Zhiqing Wei, Fengyun Li, Haotian Liu, Xu Chen, Huici Wu, Kaifeng Han, Zhiyong Feng

TL;DR

It is 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.

Abstract

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.

A 5G DMRS-based Signal for Integrated Sensing and Communication System

TL;DR

It is 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.

Abstract

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.
Paper Structure (11 sections, 1 theorem, 25 equations, 7 figures, 1 table)

This paper contains 11 sections, 1 theorem, 25 equations, 7 figures, 1 table.

Table of Contents

  1. Introduction
  2. ISAC Signal Model
  3. Time-frequency Domain Mapping Scheme of DMRS
  4. The Transmitted and Received Signal Model
  5. Sensing Performance Analysis
  6. Resolution of Distance and Velocity Estimation
  7. CRLB of Distance and Velocity Estimation
  8. Simulation Results and Analysis
  9. Distance Estimation
  10. Velocity Estimation
  11. Conclusion

Key Result

Theorem 1

The CRLBs of DMRS for distance and velocity estimation are with $\gamma=\frac{A^2}{\sigma ^2}$ is the signal-to-noise ratio (SNR).

Figures (7)

  • Figure 1: Single DMRS symbol plus three additional DMRS symbols
  • Figure 2: Comparison of RMSEs for distance estimations among PRS, DMRS, and data signal
  • Figure 3: RMSE for distance estimation under different subcarrier spacings
  • Figure 4: The velocity estimation of the proposed ISAC signal
  • Figure 5: Comparison of RMSEs for velocity estimations among PRS, DMRS and data signal
  • ...and 2 more figures

Theorems & Definitions (2)

  • Theorem 1
  • proof