Lvxin Xu

Lvxin Xu

Communication Researcher / AI and Hardware Lover

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portfolio

publications

Shifting the ISAC Trade-Off With Fluid Antenna Systems

Published in IEEE Wireless Communications Letter, 2024

As an emerging reconfigurable antenna technology, fluid antenna system (FAS) has the capability of improving both sensing and communication (S&C) performance by switching the antenna position over the available ports. This increased spatial degree-of-freedom (DoF) by FAS can be translated into enlarging the trade-off region for integrated sensing and communication (ISAC). In this letter, we propose a signal model for FAS-enabled ISAC and jointly optimize the transmit beamforming and port selection of FAS. In particular, our objective is to minimize the transmit power, while satisfying both communication and sensing requirements. To tackle this, an efficient iterative algorithm based on sparse optimization, convex approximation, and a penalty approach is developed. Our simulation results illustrate that the proposed scheme can attain 33% reductions in the transmit power with guaranteed S&C performance, showing the great potential of FAS for striking a balance between S&C in ISAC systems.

Recommended citation: J. Zou et al., "Shifting the ISAC Trade-Off With Fluid Antenna Systems," in IEEE Wireless Communications Letters, vol. 13, no. 12, pp. 3479-3483, Dec. 2024, doi: 10.1109/LWC.2024.3473991.
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Semantic Communication for VR Music Live Streaming With Rate Splitting

Published in IEEE Transactions on Computational Social Systems, 2024

Virtual reality (VR) live streaming has established a remarkable transformation of music performances that facilitates a unique interaction between artists and their audiences within a virtual environment, offering an experience that significantly surpasses the conventional constraints of live music events. This article proposes a novel framework for enhancing VR music live streaming through the integration of semantic communication and rate splitting. The framework aims to improve user experience by efficiently transmitting music and speech components. It utilizes a semantic encoder to separately extract semantic information for music and speech, to capture the unique characteristics of music and speech. After having the extracted feature, we propose a rate-splitting-based algorithm in the transmission of music and speech to enhance user utility by designating music as a common message for all users and speech as a private message targeted to specific users based on their preferences. Simulation results demonstrate significant performance gain compared to the baseline methods.

Recommended citation: J. Zou, L. Xu and S. Sun, "Semantic Communication for VR Music Live Streaming With Rate Splitting," in IEEE Transactions on Computational Social Systems, vol. 12, no. 2, pp. 918-927, April 2025, doi: 10.1109/TCSS.2024.3443176.
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Joint Port Selection and Cramer-Rao Bound Optimization for ISAC in Fluid Antenna System

Published in IEEE International Conference on Communications, 2025

Integrated sensing and communication (ISAC) has been envisioned as a key enabler for next-generation wireless systems. Meanwhile, fluid antenna system (FAS) has emerged as a promising flexible antenna technology, offering enhanced multiple access capabilities and significant spatial diversity gains. This paper studies the problem of joint port selection and Cramer-Rao Bound (CRB) optimization in an ISAC-enabled FAS. Specifically, the objective is to minimize the CRB while ensuring compliance with communication quality of service (QoS) requirements, transmit power constraints, and port selection limitations. To address this problem, we propose an iterative optimization algorithm leveraging the majorization-minimization (MM) and block coordinate descent (BCD) methods. Numerical results validate the effectiveness of the proposed algorithm, demonstrating its ability to achieve near-optimal solutions with efficient search.

Recommended citation: L. Xu, J. Zou, S. Sun and J. Wang, "Joint Port Selection and Cramér-Rao Bound Optimization for ISAC in Fluid Antenna System," ICC 2025 - IEEE International Conference on Communications, Montreal, QC, Canada, 2025, pp. 4505-4510, doi: 10.1109/ICC52391.2025.11161050.
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Secrecy Rate Maximization via Joint Robust Beamforming and Trajectory Optimization for Mobile User in ISAC-UAV System

Published in Drones, 2025

Unmanned aerial vehicles (UAVs) have emerged as a promising platform for integrated sensing and communication (ISAC) due to their mobility and deployment flexibility. By adaptively adjusting their flight trajectories, UAVs can maintain favorable line-of-sight (LoS) communication links and sensing angles, thus enhancing overall system performance in dynamic and complex environments. However, ensuring physical layer security (PLS) in such UAV-assisted ISAC systems remains a significant challenge, particularly in the presence of mobile users and potential eavesdroppers. This manuscript proposes a joint optimization framework that simultaneously designs robust transmit beamforming and UAV trajectories to secure downlink communication for multiple ground users. At each time slot, the UAV predicts user positions and maximizes the secrecy sum-rate, subject to constraints on total transmit power, multi-target sensing quality, and UAV mobility. To tackle this non-convex problem, we develop an efficient optimization algorithm based on successive convex approximation (SCA) and constrained optimization by linear approximations (COBYLA). Numerical simulations validate that the proposed framework effectively enhances the secrecy performance while maintaining high-quality sensing, achieving near-optimal performance under realistic system constraints.

Recommended citation: Xu L, Zhang Z, Yin L. Secrecy Rate Maximization via Joint Robust Beamforming and Trajectory Optimization for Mobile User in ISAC-UAV System. Drones. 2025; 9(8):536. https://doi.org/10.3390/drones9080536
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talks

teaching

Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

This is a description of a teaching experience. You can use markdown like any other post.