Toward Quantum-Enhanced ISAC: Active-RIS-Aided Integrated Sensing and Communication with Rydberg Atomic Receivers

Technical Summary: Toward Quantum-Enhanced ISAC: Active-RIS-Aided Integrated Sensing and Communication with Rydberg Atomic Receivers

Problem Statement
Integrated Sensing and Communication (ISAC) is a cornerstone of 6G networks, yet it faces fundamental trade-offs between communication quality-of-service (QoS) and sensing accuracy. Conventional ISAC systems rely on passive Reconfigurable Intelligent Surfaces (PRIS) and classical Radio-Frequency (RF) receivers. PRIS suffers from a "multiplicative fading effect," where cascaded path losses severely attenuate signals, limiting performance gains. Furthermore, classical RF receivers are constrained by Johnson-Nyquist thermal noise (JNTN) and wavelength-dependent antenna structures, creating sensitivity bottlenecks in weak-signal regimes and limiting frequency flexibility. While Active RIS (ARIS) has been proposed to mitigate path loss through amplification, and Rydberg Atomic Receivers (RARE) have emerged as a quantum sensing technology offering ultra-high sensitivity and broadband operation, a unified framework integrating ARIS and RARE for ISAC has not been investigated. Specifically, existing RARE studies focus on receiver design assuming fixed propagation environments, failing to leverage propagation-domain degrees of freedom (DoF) to enhance echo signals or suppress interference.

Methodology
The paper proposes a unified ARIS-aided ISAC framework where a dual-functional Base Station (BS) serves multiple users and performs radar sensing, utilizing RAREs at both the user terminals and the BS sensing receiver.

1. System Modeling:

   • Signal Model: The authors derive a unified model incorporating the unique characteristics of RARE. Unlike complex RF signals, RAREs perform magnitude-only, real-domain observations via Electromagnetically Induced Transparency (EIT) and Autler-Townes (AT) splitting. Under a strong-reference regime, the nonlinear optical measurement is linearized to a real-valued projection of the effective channel.
   • Noise Characterization: The model accounts for RARE-specific quantum shot noise (QSN), which is significantly lower than thermal noise, as well as amplified noise from the ARIS.
   • CRB Derivation: A closed-form Cramér-Rao Bound (CRB) for Direction-of-Arrival (DoA) estimation is derived. This formulation explicitly captures the impact of ARIS-induced channel shaping, amplified noise propagation, and the specific real-domain measurement structure of RARE.

2. Optimization Framework:

   • Problem Formulation: The authors formulate a joint design problem to minimize the DoA estimation CRB subject to BS transmit power, ARIS power consumption (including amplification and circuit power), and user SINR constraints. The problem is highly non-convex due to the fractional CRB objective and coupled constraints.
   • Alternating Optimization (AO): To solve this, an AO framework is developed:
     • Beamforming Design (BS): For a fixed ARIS configuration, the transmit beamforming covariance matrix is optimized. The non-convex fractional objective is transformed into a tractable Semidefinite Relaxation (SDR) problem using the Schur complement, resulting in a convex Semidefinite Program (SDP).
     • ARIS Design: For a fixed beamforming vector, the ARIS reflection coefficients are optimized. A Majorization-Minimization (MM) approach is employed to handle the non-convex unit-modulus and power-coupled constraints. A tight surrogate function is constructed to upper-bound the objective, enabling low-complexity element-wise updates with guaranteed monotonic improvement.

Key Contributions

• Unified Framework: The paper establishes the first system-level framework integrating ARIS and RARE for ISAC, simultaneously addressing propagation limitations (via ARIS) and receiver sensitivity limits (via RARE).
• RARE-Aware Modeling: It characterizes the unique magnitude-only, real-domain observation structure of RARE, demonstrating that communication information is intrinsically embedded in power-domain observations.
• Closed-Form CRB: A novel closed-form CRB for DoA estimation is derived, explicitly modeling the interplay between ARIS amplification, noise propagation, and RARE measurement characteristics.
• Algorithmic Innovation: The development of a structured AO framework combining SDR for beamforming and MM for ARIS design provides an efficient solution to the resulting non-convex optimization problem.

Results
Numerical simulations demonstrate that the proposed RARE-enabled ARIS-ISAC framework consistently outperforms conventional designs based on classical RF receivers and passive RIS. Key findings include:

• Superior Performance: The proposed framework achieves significantly lower CRB (higher sensing accuracy) and better communication reliability compared to RF-based baselines.
• Benchmark Proximity: The performance approaches that of a radar-only benchmark, highlighting the efficacy of the joint design.
• Synergy: The results validate the complementary gains of ARIS (mitigating path loss) and RARE (reducing noise floor), enabling robust echo recovery and accurate sensing even in challenging conditions.

Significance
The paper claims that this work highlights the potential of RARE for "quantum-enhanced ISAC." By explicitly incorporating the RARE-specific signal model into a propagation-aware architecture, the study reveals new design insights necessitated by the real-domain observation structure and low-noise characteristics of quantum receivers. The work suggests that jointly exploiting ARIS-driven propagation enhancement and RARE-based quantum reception can effectively overcome the fundamental limitations of classical ISAC systems, offering a pathway toward more reliable and accurate 6G sensing and communication.