arXiv subjects

Shengcai Zhou

Publications and source records attributed to Shengcai Zhou.

4 recordsLinked to original sources

arXiv2026

Extended Target Adaptive Beamforming for ISAC:A Perspective of Predictive Error Ellipse

Utilizing communication signals to extract motion parameters has emerged as a key direction in Vehicle-to- Everything (V2X) networks. Accurately modeling the relationship between communication signals and sensing performance is critical for the advancement of such systems. Unlike prior work that relies primarily on qualitative analysis, this paper derives the Cramér-Rao Bound (CRB) for radar parameter estimation in the context of Orthogonal Frequency Division Multiplexing (OFDM) waveforms and Uniform Planar Array (UPA) configurations. Recognizing that vehicles may act as extended targets, we propose two New Radio (NR)-V2X-compatible beamforming schemes tailored to different phases of the communication process. During the initial beam establishment phase, we develop a beamforming approach based on the union of predictive error ellipses, which enhances scatterer localization through temporally assisted beam training. In the beam adjustment phase, we introduce an adaptive narrowest-beam strategy that leverages the positions of scatterers and the communication receiver (CR), enabling effective tracking with reduced complexity. The beam design problem is addressed using the minimum enclosing ellipse algorithm and tailored antenna control methods. Simulation results validate the proposed approach, showing up to a 32.4% improvement in achievable rate with a 32*32 transmit antenna array and a 5.2% gain with an 8*8 array, compared to conventional beam sweeping under identical SNR conditions.

cs.IT↗

arXiv2025

Beamforming-based Achievable Rate Maximization in ISAC System for Multi-UAV Networking

Airborne mobile Integrated Sensing and Communication (ISAC) base stations have garnered significant attention recently, with ISAC technology being a crucial application for 6G networks. Since ISAC can sense potential mobile communication users, this paper studies an effective scheme for a multi-UAV network tailored for emergency communication. In this paper, we develop a temporal-assisted frame structure utilizing integrated omnidirectional and directional beampattern to facilitate efficient and frequent searching, with extended Kalman filtering (EKF) as an aid to beam alignment. Further, we address an optimization problem to maximize the total achievable rate per slot by jointly designing UAV beamforming, load management, and UAV direction planning, all while adhering to the constraints of the predicted beam coverage. Given the problem NP-hard, we introduce three robust mechanisms for its resolution: an enhanced distributed Successive Convex Approximation (SCA)-Iterative Rank Minimization (IRM) algorithm, an coalition game approach, and a Fermat point search method. In particular, the proposed SCA-IRM algorithm decomposes the original complex optimization problem into several sub-problems and assigns them equally to each UAV, so as to realize distributed computing and improve computational efficiency. Our proposed simulations demonstrate the improved system performance in terms of communication rate, fairness, and sensing accuracy, providing design guidelines of UAV-assisted emergency communication networking.

cs.PF↗

arXiv2024

Temporal-Assisted Beamforming and Trajectory Prediction in Sensing-Enabled UAV Communications

In the evolving landscape of high-speed communication, the shift from traditional pilot-based methods to a Sensing-Oriented Approach (SOA) is anticipated to gain momentum. This paper delves into the development of an innovative Integrated Sensing and Communication (ISAC) framework, specifically tailored for beamforming and trajectory prediction processes. Central to this research is the exploration of an Unmanned Aerial Vehicle (UAV)-enabled communication system, which seamlessly integrates ISAC technology. This integration underscores the synergistic interplay between sensing and communication capabilities. The proposed system initially deploys omnidirectional beams for the sensing-focused phase, subsequently transitioning to directional beams for precise object tracking. This process incorporates an Extended Kalman Filtering (EKF) methodology for the accurate estimation and prediction of object states. A novel frame structure is introduced, employing historical sensing data to optimize beamforming in real-time for subsequent time slots, a strategy we refer to as 'temporal-assisted' beamforming. To refine the temporal-assisted beamforming technique, we employ Successive Convex Approximation (SCA) in tandem with Iterative Rank Minimization (IRM), yielding high-quality suboptimal solutions. Comparative analysis with conventional pilot-based systems reveals that our approach yields a substantial improvement of 156\% in multi-object scenarios and 136\% in single-object scenarios.

math.NA↗

arXiv2024

Temporal-Assisted Dynamic Beampattern Optimization in Integrated Sensing and Communication Systems

In this paper, an integrated sensing and communication (ISAC) system is investigated. Initially, we introduce a design criterion wherein sensing data acquired from the preceding time slot is employed for instantaneous optimal beamforming in the succeeding time slot, aiming to enhance the communication rate. Subsequently, the development of optimal beamforming is addressed, and a high-caliber suboptimal resolution is derived utilizing successive convex approximation (SCA) techniques combined with the iterative rank minimization (IRM) methodology. Our evaluations, grounded on numerical analyses, reveal that the communication rate of the introduced beamforming strategy surpasses that of conventional omnidirectional sensing and pilot based approaches.

cs.CG↗