OTFS-ISAC System with Sub-Nyquist ADC Sampling Rate

TL;DR

This paper introduces an OTFS-based ISAC system that operates at sub-Nyquist ADC sampling rates, enabling accurate radar sensing and reliable communication while significantly reducing hardware costs.

Contribution

It proposes a novel OTFS-ISAC architecture with pilot symbols in the DD domain and an iterative interference cancellation algorithm for low-rate sampling.

Findings

Achieves accurate radar estimation at reduced sampling rates.

Maintains reliable communication with lower hardware costs.

Validated through SDR-based experiments.

Abstract

Integrated sensing and communication (ISAC) has emerged as a pivotal technology for next-generation wireless communication and radar systems, enabling high-resolution sensing and high-throughput communication with shared spectrum and hardware. However, achieving a fine radar resolution often requires high-rate analog-to-digital converters (ADCs) and substantial storage, making it both expensive and impractical for many commercial applications. To address these challenges, this paper proposes an orthogonal time frequency space (OTFS)-based ISAC architecture that operates at reduced ADC sampling rates, yet preserves accurate radar estimation and supports simultaneous communication. The proposed architecture introduces pilot symbols directly in the delay-Doppler (DD) domain to leverage the transformation mapping between the DD and time-frequency (TF) domains to keep selected subcarriers active while others are inactive, allowing the radar receiver to exploit under-sampling aliasing and recover the original DD signal at much lower sampling rates. To further enhance the radar accuracy, we develop an iterative interference estimation and cancellation algorithm that mitigates data symbol interference. We propose a code-based spreading technique that distributes data across the DD domain to preserve the maximum unambiguous radar sensing range. For communication, we implement a complete transceiver pipeline optimized for reduced sampling rate system, including synchronization, channel estimation, and iterative data detection. Experimental results from a software-defined radio (SDR)-based testbed confirm that our method substantially lowers the required sampling rate without sacrificing radar sensing performance and ensures reliable communication.