arXiv subjects

Haobin Mao

Publications and source records attributed to Haobin Mao.

6 recordsLinked to original sources

arXiv2026

Evaluating AI Grading on Real-World Handwritten College Mathematics: A Large-Scale Study Toward a Benchmark

Grading in large undergraduate STEM courses often yields minimal feedback due to heavy instructional workloads. We present a large-scale empirical study of AI grading on real, handwritten single-variable calculus work from UC Irvine. Using OCR-conditioned large language models with structured, rubric-guided prompting, our system produces scores and formative feedback for thousands of free-response quiz submissions from nearly 800 students. In a setting with no single ground-truth label, we evaluate performance against official teaching-assistant grades, student surveys, and independent human review, finding strong alignment with TA scoring and a large majority of AI-generated feedback rated as correct or acceptable across quizzes. Beyond calculus, this setting highlights core challenges in OCR-conditioned mathematical reasoning and partial-credit assessment. We analyze key failure modes, propose practical rubric- and prompt-design principles, and introduce a multi-perspective evaluation protocol for reliable, real-course deployment. Building on the dataset and evaluation framework developed here, we outline a standardized benchmark for AI grading of handwritten mathematics to support reproducible comparison and future research.

cs.LG↗

arXiv2025

Movable-Antenna Array Enhanced Multi-Target Sensing: CRB Characterization and Optimization

Movable antennas (MAs) have emerged as a promising technology to improve wireless communication and sensing performance towards sixth-generation (6G) networks through flexible antenna movement. In this paper, we propose a novel wireless sensing system based on MA arrays to enhance multi-target spatial angle estimation performance. We begin by characterizing the Cram\'{e}r-Rao bound (CRB) matrix for multi-target angle of arrival (AoA) estimation as a function of the antenna's positions in MA arrays, thereby establishing a theoretical foundation for antenna position optimization. Then, aiming at improving the sensing coverage performance, we formulate an optimization problem to minimize the expectation of the trace of the CRB matrix over random target angles subject to a given distribution by optimizing the antennas' positions. To tackle the formulated challenging optimization problem, the Monte Carlo method is employed to approximate the intractable objective function, and a swarm-based gradient descent algorithm is subsequently proposed to address the approximated problem. In addition, a lower-bound on the sum of CRBs for multi-target AoA estimation is derived. Numerical results demonstrate that the proposed MA-based design achieves superior sensing performance compared to conventional systems using fixed-position antenna (FPA) arrays and single-target-oriented MA arrays, in terms of decreasing both CRB and the actual AoA estimation mean square error (MSE). Fundamentally, the designed MA array geometry exhibits low correlation and high effective power of sensitivity vectors for multi-target sensing in the angular domain, leading to significant CRB performance improvement. The resultant low correlation of steering vectors over multiple targets' directions further helps mitigate angle estimation ambiguity and thus enhances MSE performance.

eess.SP↗

arXiv2025

Movable and Reconfigurable Antennas for 6G: Unlocking Electromagnetic-Domain Design and Optimization

The growing demands of 6G mobile communication networks necessitate advanced antenna technologies. Movable antennas (MAs) and reconfigurable antennas (RAs) enable dynamic control over antenna's position, orientation, radiation, polarization, and frequency response, introducing rich electromagnetic-domain degrees of freedom for the design and performance enhancement of wireless systems. This article overviews their application scenarios, hardware architectures, and design methods. Field test and simulation results highlight their performance benefits over conventional fixed/non-reconfigurable antennas.

cs.IT↗

arXiv2025

Towed Movable Antenna (ToMA) Array for Ultra Secure Airborne Communications

This paper proposes a novel towed movable antenna (ToMA) array architecture to enhance the physical layer security of airborne communication systems. Unlike conventional onboard arrays with fixed-position antennas (FPAs), the ToMA array employs multiple subarrays mounted on flexible cables and towed by distributed drones, enabling agile deployment in three-dimensional (3D) space surrounding the central aircraft. This design significantly enlarges the effective array aperture and allows dynamic geometry reconfiguration, offering superior spatial resolution and beamforming flexibility. We consider a secure transmission scenario where an airborne transmitter communicates with multiple legitimate users in the presence of potential eavesdroppers. To ensure security, zero-forcing beamforming is employed to nullify signal leakage toward eavesdroppers. Based on the statistical distributions of locations of users and eavesdroppers, the antenna position vector (APV) of the ToMA array is optimized to maximize the users' ergodic achievable rate. Analytical results for the case of a single user and a single eavesdropper reveal the optimal APV structure that minimizes their channel correlation. For the general multiuser scenario, we develop a low-complexity alternating optimization algorithm by leveraging Riemannian manifold optimization. Simulation results confirm that the proposed ToMA array achieves significant performance gains over conventional onboard FPA arrays, especially in scenarios where eavesdroppers are closely located to users under line-of-sight (LoS)-dominant channels.

cs.IT↗

arXiv2024

6D Movable Antenna Enhanced Multi-Access Point Coordination via Position and Orientation Optimization

The effective utilization of unlicensed spectrum is regarded as an important direction to enable the massive access and broad coverage for next-generation wireless local area network (WLAN). Due to the crowded spectrum occupancy and dense user terminals (UTs), the conventional fixed antenna (FA)-based access points (APs) face huge challenges in realizing massive access and interference cancellation. To address this issue, in this paper we develop a six-dimensional movable antenna (6DMA) enhanced multi-AP coordination system for coverage enhancement and interference mitigation. First, we model the wireless channels between the APs and UTs to characterize their variation with respect to 6DMA movement, in terms of both the three-dimensional (3D) position and 3D orientation of each distributed AP's antenna. Then, an optimization problem is formulated to maximize the weighted sum rate of multiple UTs for their uplink transmissions by jointly optimizing the antenna position vector (APV), the antenna orientation matrix (AOM), and the receive combining matrix over all coordinated APs, subject to the constraints on local antenna movement regions. To solve this challenging non-convex optimization problem, we first transform it into a more tractable Lagrangian dual problem. Then, an alternating optimization (AO)-based algorithm is developed by iteratively optimizing the APV and AOM, which are designed by applying the successive convex approximation (SCA) technique and Riemannian manifold optimization-based algorithm, respectively. Simulation results show that the proposed 6DMA-enhanced multi-AP coordination system can significantly enhance network capacity, and both of the online and offline 6DMA schemes can attain considerable performance improvement compared to the conventional FA-based schemes.

eess.SP↗

arXiv2024

Sum Rate Maximization for Movable Antenna Enhanced Multiuser Covert Communications

In this letter, we propose to employ movable antenna (MA) to enhance covert communications with noise uncertainty, where the confidential data is transmitted from an MA-aided access point (AP) to multiple users with a warden attempting to detect the existence of the legal transmission. To maximize the sum rate of users under covertness constraint, we formulate an optimization problem to jointly design the transmit beamforming and the positions of MAs at the AP. To solve the formulated non-convex optimization problem, we develop a block successive upper-bound minimization (BSUM) based algorithm, where the proximal distance algorithm (PDA) and the successive convex approximation (SCA) are employed to optimize the transmit beamforming and the MAs' positions, respectively. Simulation results show that the proposed MAs-aided system can significantly increase the covert sum rate via antenna position optimization as compared to conventional systems with fixed-position antennas (FPAs).

eess.SP↗