arXiv subjects

Changhao He

Publications and source records attributed to Changhao He.

5 recordsLinked to original sources

arXiv2026

Cram\'er-Rao Bound Analysis for Cell-Free ISAC Systems with Fluid Intelligent Metasurfaces

Fluid intelligent metasurface (FIM) is an emerging antenna architecture that continuously reshapes its physical geometry to optimize wireless performance. While existing studies on FIM-aided integrated sensing and communication (ISAC) rely on co-located single-base-station (BS) deployments, they fundamentally underutilize FIM's morphological flexibility due to restricted observation angles. In this paper, we investigate a FIM-augmented cell-free ISAC architecture, where distributed access points (APs) collaboratively observe a target from diverse angles. We derive the complete Fisher information matrix for target angle estimation and obtain a closed-form localization CRB that explicitly quantifies the angular diversity gain. By analyzing the block structure of the Fisher information matrix, we uncover three cell-free-specific phenomena: (i) cross-AP information coupling, (ii) multiplicative Tx--Rx FIM coupling, and (iii) angular diversity amplification. Under a 28\,GHz configuration with four APs and eight FIM elements per AP, our analysis shows that distributed angular diversity amplifies the FIM morphing gain to 15.8\,dB, compared to only 0.4\,dB in a single-AP pair deployment with the same total antenna count. We further propose an alternating optimization algorithm for joint beamforming and FIM shape design via semidefinite relaxation whose tightness is formally proved. Numerical results confirm that the proposed cell-free FIM-ISAC architecture achieves a 4.5\,dB localization CRB reduction over the single-AP fixed-array baseline at 10\,dB sensing SNR while maintaining communication quality-of-service constraints across the entire Pareto frontier.

cs.IT↗

arXiv2026

RA-CAD: Learning Post-Execution Critique for State-Aware Text-to-CAD Generation

Text-to-CAD generation translates natural-language design intent into editable and executable parametric computer-aided design (CAD) codes, reducing the expertise and effort required for manual modeling. Existing methods incorporate fixed, externally supplied, prompt-induced, or separately optimized critique mechanisms to optimize the generation process, but they do not necessarily optimize how feedback is interpreted and translated into effective corrective actions throughout the generation process. To bridge this feedback-utilization gap, we present RA-CAD (ReAct Agent for CAD), a state-aware agent that interacts with the CAD environment through a Generate--Execute--Critique--Rewrite loop. At each iteration, RA-CAD executes the current code and observes its outcome. Conditioned on the design instruction, current code, and execution feedback, the agent then generates an explicit post-execution critique as an intermediate policy action. This critique either validates the current result for termination or provides revision-oriented guidance that conditions the next rewrite. CAD Code Bootstrapping (CCB) first establishes fundamental parametric CAD coding capabilities through supervised fine-tuning. Feedback-Driven Agent Optimization (FAO) subsequently applies trajectory-level Group Relative Policy Optimization to both policy-generated code and critique sequences, assigning terminal F1 and Chamfer Distance rewards to the complete interaction trajectory. This formulation makes critique an outcome-aligned, learnable policy decision rather than an unoptimized auxiliary output. Experiments on CADFusion and Text2CAD show that RA-CAD achieves state-of-the-art execution validity and geometric quality compared with existing methods and strong proprietary language models, demonstrating the effectiveness of the proposed state-aware text-to-CAD agent.

cs.AI↗

arXiv2026

Visibility-Region Coupling in XL-MIMO AGV Fleets: Triple-Role Modeling and Masked Beamforming

Extremely large-scale multiple-input multiple-output (XL-MIMO) is a promising technology for supporting automated guided vehicle (AGV) fleets in smart port terminals. However, the metallic container environment induces spatial non-stationarity, whereby each AGV is visible to only a subset of the array, referred to as its visibility region (VR). Unlike existing XL-MIMO models that assume user-independent VRs, we show that each AGV simultaneously acts as a communication user, a metallic scatterer, and a blocker, resulting in coupled user channels and VRs. We formulate this \emph{triple-role} effect through a VR-coupled channel model and develop a VR-aware downlink beamforming framework based on masked weighted minimum mean-square error (WMMSE), where the masking operation exactly enforces VR support constraints while significantly reducing computational complexity. Simulation results in a realistic smart port scenario demonstrate more than a threefold sum-rate improvement over VR-unaware baselines, with the gains becoming increasingly pronounced as fleet density increases.

cs.IT↗

arXiv2026

A Unified Dual Framework for Sparse-Array Near-Field Beam Focusing With Spatial Interference Suppression

We study sparse-array near-field beam focusing with spatial interference suppression, a problem arising in coherent satellite formations and other distributed non-terrestrial arrays. State-of-the-art designs solve it numerically through second-order cone programming (SOCP) with cutting-plane refinement, yet the achievable signal-to-interference ratio (SIR) and its link to classical adaptive beamforming have remained without an analytical characterization. We supply this characterization via a Lagrangian-dual analysis, obtaining three results. First, every optimal beamformer is a generalized matched filter against an effective spatial covariance induced by an optimal dual measure; this closed form recovers MVDR, LCMV, and SOCP-based focusing as special cases. Second, the dual measure has finite support of cardinality at most $M^2$ in general, sharpening to $M$ for uniform linear arrays ($M$ the number of array elements), which yields a finite-dimensional convergence certificate for cutting-plane methods. Third, a closed-form upper bound on the mean-SIR admits an asymptotic logarithmic scaling law in $M$ under near-collinear geometry, identifying array order, rather than the optimization algorithm, as the dominant performance factor. A Riemannian conjugate-gradient algorithm on the unit-torus manifold is developed for practical constant-modulus beamforming, and numerical results demonstrate that it closely approaches the derived performance limit.

cs.IT↗

arXiv2026

Twin-in-the-Loop Optimization and Fundamental Limits of Position--Velocity Estimation in Cell-Free ISAC Systems

Digital twin (DT) networks require tight integration with wireless sensing, yet the fundamental limits of such coupling in cell-free integrated sensing and communication (ISAC) systems remain largely unexplored, particularly in the presence of fluid intelligent metasurfaces (FIM). This paper establishes a joint position-velocity Cramer-Rao bound (CRB) framework, operationalized through a twin-in-the-loop architecture. By leveraging a scatter-matrix decomposition of the velocity Fisher information, we show that single-base-station systems are inherently rank-deficient for two-dimensional velocity estimation, whereas cell-free deployments with multiple access-point pairs achieve full observability. The resulting CRB reveals a spatio-temporal decoupling: FIM shape optimization significantly improves position accuracy but does not affect the velocity CRB under isotropic waveforms while Doppler coupling asymmetrically enhances position estimation accuracy. Building on this analysis, we develop a closed-loop DT framework, deriving the critical mismatch angle in closed form and showing that angular diversity in cell-free systems mitigates DT prediction errors. We further characterize the optimal synchronization period and propose a confidence-aware scheduling strategy that reduces the DT update rate. Numerical results demonstrate substantial performance gains over single-base-station systems, with improvements attributed to angular diversity, Doppler-position coupling, and FIM adaptation.

cs.IT↗