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Signal Design for OTFS Dual-Functional Radar and Communications with Imperfect CSI

Borui Du, Yumeng Zhang, Christos Masouros, Bruno Clerckx

TL;DR

This work tackles DFRC design for OTFS under imperfect CSI by jointly optimizing pilot symbols and data power using a tractable channel-capacity lower bound and an integrated sidelobe level (ISL) radar metric. A two-tier optimization combines an OTFS SINR-focused communication objective with ISL-based sensing, solved through alternating optimization augmented with ADMM-SCA to handle nonconvexities. The proposed method expands the feasible sensing-communication region, delivering substantial gains in ISL suppression and SINR while improving BER performance, demonstrating the practical viability of DFRC-OTFS in high-mobility scenarios. Overall, the study provides a rigorous framework for joint pilot-data design under CSI uncertainty, with explicit metrics and an algorithmic pathway that can guide real-world ISAC deployments.

Abstract

Orthogonal time frequency space (OTFS) offers significant advantages in managing mobility for both wireless sensing and communication systems, making it a promising candidate for dual-functional radar-communication (DFRC). However, the optimal signal design that fully exploits OTFS's potential in DFRC has not been sufficiently explored. This paper addresses this gap by formulating an optimization problem for signal design in DFRC-OTFS, incorporating both pilot-symbol design for channel estimation and data-power allocation. Specifically, we employ the integrated sidelobe level (ISL) of the ambiguity function as a radar metric, accounting for the randomness of the data symbols alongside the deterministic pilot symbols. For communication, we derive a channel capacity lower bound metric that considers channel estimation errors in OTFS. We maximize the weighted sum of sensing and communication metrics and solve the optimization problem via an alternating optimization framework. Simulations indicate that the proposed signal significantly improves the sensing-communication performance region compared with conventional signal schemes, achieving at least a 9.44 dB gain in ISL suppression for sensing, and a 4.82 dB gain in the signal-to-interference-plus-noise ratio (SINR) for communication.

Signal Design for OTFS Dual-Functional Radar and Communications with Imperfect CSI

TL;DR

This work tackles DFRC design for OTFS under imperfect CSI by jointly optimizing pilot symbols and data power using a tractable channel-capacity lower bound and an integrated sidelobe level (ISL) radar metric. A two-tier optimization combines an OTFS SINR-focused communication objective with ISL-based sensing, solved through alternating optimization augmented with ADMM-SCA to handle nonconvexities. The proposed method expands the feasible sensing-communication region, delivering substantial gains in ISL suppression and SINR while improving BER performance, demonstrating the practical viability of DFRC-OTFS in high-mobility scenarios. Overall, the study provides a rigorous framework for joint pilot-data design under CSI uncertainty, with explicit metrics and an algorithmic pathway that can guide real-world ISAC deployments.

Abstract

Orthogonal time frequency space (OTFS) offers significant advantages in managing mobility for both wireless sensing and communication systems, making it a promising candidate for dual-functional radar-communication (DFRC). However, the optimal signal design that fully exploits OTFS's potential in DFRC has not been sufficiently explored. This paper addresses this gap by formulating an optimization problem for signal design in DFRC-OTFS, incorporating both pilot-symbol design for channel estimation and data-power allocation. Specifically, we employ the integrated sidelobe level (ISL) of the ambiguity function as a radar metric, accounting for the randomness of the data symbols alongside the deterministic pilot symbols. For communication, we derive a channel capacity lower bound metric that considers channel estimation errors in OTFS. We maximize the weighted sum of sensing and communication metrics and solve the optimization problem via an alternating optimization framework. Simulations indicate that the proposed signal significantly improves the sensing-communication performance region compared with conventional signal schemes, achieving at least a 9.44 dB gain in ISL suppression for sensing, and a 4.82 dB gain in the signal-to-interference-plus-noise ratio (SINR) for communication.
Paper Structure (13 sections, 22 equations, 5 figures)

This paper contains 13 sections, 22 equations, 5 figures.

Table of Contents

  1. Introduction
  2. System and Signal Model
  3. Transmitted Signal Model
  4. High-Mobility Communication Channel Model
  5. Received Signal Model at the Communication Receiver
  6. Performance Metrics
  7. Channel Capacity Lower Bound
  8. Integrated Sidelobe Level of the Ambiguity Function
  9. Optimization for Signal Design
  10. Problem Formulation
  11. Alternating Optimization
  12. Numerical Results
  13. Conclusion

Figures (5)

  • Figure 1: A toy example that illustrates the symbol arrangement (i.e., $\mathbf{\Phi}_{\text{p}}$, $\mathbf{\Phi}_{\text{c}}$) and modulation process in the OTFS framework.
  • Figure 2: Spike, flat, and cluster arrangements in the DD domain.
  • Figure 3: The achievable DFRC performance region (each metric is normalized to its optimal value at $\eta=1$ during optimization, and is displayed on its original scale). Flat and cluster schemes employ $r_\text{GI}=0.5$ and $r_\text{pilot}=0.375$.
  • Figure 4: Empirical AFs of optimization results across different ISAC balance parameters to verify our proposed radar metric.
  • Figure 5: Monte Carlo results for the optimized, cluster, and flat arrangements with estimated CSI ($\eta=1$, $r_{\text{GI}}=0.5$, $r_{\text{pilot}}=0.375$; $L=7$, $Q=3$; $5\times10^{5}$ trials).