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Outage-Aware Online Prediction Control for Securing UAV-Aided communication

IEEE Transactions on Vehicular Technology 2025年

作者： Sheng, Zhichao Fu, Huabo Huang, Zhiyu Nasir, Ali A. Wu, Qingqing Zeng, Dan Shanghai University Shanghai Institute for Advanced Communication and Data Science Key Laboratory of Specialty Fiber Optics and Optical Access Networks Shanghai200444 China Department of Electrical Engineering and Center for Communication Systems and Sensing Dhahran31261 Saudi Arabia Shanghai Jiao Tong University Department of Electronic Engineering Shanghai201210 China

Considering an unmanned aerial vehicle (UAV)-aided multi-user system with multiple mobile eavesdroppers, this paper aims to develop an outage-aware online control strategy to counter the imperfect information of mobile user equipments (UEs) and mobile eavesdroppers. To perform online control effectively, a novel online prediction model is proposed, which models the trajectory of UEs as a stochastic Gauss-Markov mobility model and the trajectory of eavesdroppers as a worst-case model based on the current imperfect location information. The online control problem is formulated as a new multi-stage optimization framework, in which we perform online control by solving per-slot prediction problems and a resource allocation problem for the initial point. In the per-slot prediction problem, we jointly optimize the predictive trajectory and transmit power for the upcoming time slot (TS) by maximizing the minimum achievable secrecy rate (ASR) among all UEs. For resource allocation at the initial TS, we optimize transmit power by maximizing the minimum ASR among all UEs. The per-slot prediction problems and the resources allocation problem are all non-convex problems hence they are intractable in terms of computational complexity. To address them, we propose an efficient inner-approximation methods, by applying successive convex approximation (SCA) methods and S-procedure as well as Bernstein -type inequality. Numerical results demonstrate the superiority of our proposed online control scheme over the conventional benchmark schemes which include existing offline schemes and online scheme without outage based prediction as well as shortest-path navigation scheme. © 1967-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation with Ultra-Low Sampling Rate by Diffusion Models

arXiv

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arXiv 2025年

作者： Liu, Zhiyuan Zhang, Shuhang Liu, Qingyu Zhang, Hongliang Song, Lingyang School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China Pengcheng Laboratory Shenzhen518055 China Department of Electronics Peking University Beijing100871 China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China

Fine-grained radio map presents communication parameters of interest, e.g., received signal strength, at every point across a large geographical region. It can be leveraged to improve the efficiency of spectrum utilization for a large area, particularly critical for the unlicensed WiFi spectrum. The problem of fine-grained radio map estimation is to utilize radio samples collected by sparsely distributed sensors to infer the map. This problem is challenging due to the ultra-low sampling rate, where the number of available samples is far less than the fine-grained resolution required for radio map estimation. We propose WiFi-Diffusion – a novel generative framework for achieving fine-grained WiFi radio map estimation using diffusion models. WiFi-Diffusion employs the creative power of generative AI to address the ultra-low sampling rate challenge and consists of three blocks: 1) a boost block, using prior information such as the layout of obstacles to optimize the diffusion model;2) a generation block, leveraging the diffusion model to generate a candidate set of radio maps;and 3) an election block, utilizing the radio propagation model as a guide to find the best radio map from the candidate set. Extensive simulations demonstrate that 1) the fine-grained radio map generated by WiFi-Diffusion is ten times better than those produced by state-of-the-art (SOTA) when they use the same ultra-low sampling rate;and 2) WiFi-Diffusion achieves comparable fine-grained radio map quality with only one-fifth of the sampling rate required by SOTA. Copyright © 2025, The Authors. All rights reserved.

关键词： Wi-Fi

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Velocity-comb modulation transfer spectroscopy

arXiv

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arXiv 2025年

作者： Guan, Xiaolei Xiao, Zheng Liu, Zijie Wang, Zhiyang Zhang, Jia Gao, Xun Chang, Pengyuan Shi, Tiantian Chen, Jingbiao State Key Laboratory of Advanced Optical Communication Systems and Networks Institute of Quantum Electronics School of Electronics Peking University Beijing100871 China Institute of Quantum Information and Technology Nanjing University of Posts and Telecommunications Nanjing210003 China National Key Laboratory of Advanced Micro and Nano Manufacture Technology School of Integrated Circuits Peking University Beijing100871 China Hefei National Laboratory Hefei230088 China

Sub-Doppler laser spectroscopy is a crucial technique for laser frequency stabilization, playing a significant role in atomic physics, precision measurement, and quantum communication. However, recent efforts to improve frequency stability appear to have reached a bottleneck, as they primarily focus on external technical approaches while neglecting the fundamental issue of low atomic utilization ( Copyright © 2025, The Authors. All rights reserved.

关键词： Frequency stability

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Bidirectional radio-over-fiber systems with SSB modulation and wavelength reuse based on injection-locked semiconductor lasers

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Chinese Optics Letters 2010年第11期8卷 1040-1042页

作者：洪成张诚段俊胡薇薇徐安士陈章渊 State Key Laboratory of Advanced Optical Communication Systems and Networks Peking University

A 60-GHz bidirectional radio-over-fiber （RoF） system using two-carrier-injected distributed feedback （DFB） laser is proposed and demonstrated to realize optical single sideband （SSB） modulation for *** injection-locked Fabry-P＇erot laser is also carried out to realize wavelength reuse in *** of 2.5 Gb/s on a 60-GHz carrier for downlink and 622-Mb/s baseband signal for uplink are both successfully demonstrated over 50-km single mode fiber without chromatic dispersion compensation.

关键词： Electromagnetic dispersion Feedback Lasers Single mode fibers

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Coherent optical OFDM scheme with inter-carrier interference self-cancellation and common phase error compensation

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Chinese Optics Letters 2010年第7期8卷 634-638页

作者：吴毅凌李巨浩赵春旭赵玉萍张帆陈章渊 State Key Laboratory of Advanced Optical Communication Systems & Networks Peking University

Schemes integrating inter-carrier interference （ICI） self-cancellation and common phase error （CPE） com- pensation for coherent optical orthogonal frequency division multiplexing （CO-OFDM） systems are investi- gated. The purpose of our research is to counteract the impacts of laser phase noise and fiber nonlinearity. We propose two ICI self-cancellation-based CO-OFDM schemes, and adopt a pilot-aided decision feedback （DFB） loop for CPE compensation. The proposed schemes are compared with conventional CO-OFDM schemes at the same spectral efficiency. Simulations show that our schemes can not only enhance laser linewidth tolerance of the CO-OFDM system, but also present strong robustness against fiber nonlinearity.

关键词： Error compensation Frequency allocation Orthogonal functions Spectrum analyzers Telecommunication systems

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LLM4WM: Adapting LLM for Wireless Multi-Tasking

arXiv

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arXiv 2025年

作者： Liu, Xuanyu Gao, Shijian Liu, Boxun Cheng, Xiang Yang, Liuqing State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China Guangzhou511400 China Guangzhou511400 China Department of Electronic and Computer Engineering The Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong

The wireless channel is fundamental to communication, encompassing numerous tasks collectively referred to as channel-associated tasks. These tasks can leverage joint learning based on channel characteristics to share representations and enhance system design. To capitalize on this advantage, LLM4WM is proposed—a large language model (LLM) multi-task fine-tuning framework specifically tailored for channel-associated tasks. This framework utilizes a Mixture of Experts with Low-Rank Adaptation (MoE-LoRA) approach for multi-task fine-tuning, enabling the transfer of the pre-trained LLM’s general knowledge to these tasks. Given the unique characteristics of wireless channel data, preprocessing modules, adapter modules, and multi-task output layers are designed to align the channel data with the LLM’s semantic feature space. Experiments on a channel-associated multi-task dataset demonstrate that LLM4WM outperforms existing methodologies in both full-sample and few-shot evaluations, owing to its robust multi-task joint modeling and transfer learning capabilities. Copyright © 2025, The Authors. All rights reserved.

关键词： Semantics

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Quantum neural compressive sensing for ghost imaging

arXiv

引用

arXiv 2025年

作者： Zhai, Xinliang Xiao, Tailong Huang, Jingzheng Fan, Jianping Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Institute for Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Hefei National Laboratory Hefei230088 China Shanghai Research Center for Quantum Sciences Shanghai201315 China AI Lab Lenovo Research Beijing100094 China

Demonstrating the utility of quantum algorithms is a long-standing challenge, where quantum machine learning becomes one of the most promising candidate that can be resorted to. In this study, we investigate a quantum neural compressive sensing algorithm for ghost imaging to showcase its utility. The algorithm utilizes the variational quantum circuits to reparameterize the inverse problem of ghost imaging and uses the inductive bias of the physical forward model to perform optimization. To validate the algorithm’s effectiveness, we conduct optical ghost imaging experiments, capturing signals from objects at different physical sampling rates and detection signal-to-noise ratios. The experimental results show that our proposed algorithm surpasses conventional methods in both visual appearance and quantitative metrics, achieving state-of-the-art performance. Importantly, we observe that the quantum neural network, guided by prior knowledge of physics, effectively overcomes the challenge of barren plateau in the optimization process. The proposed algorithm demonstrates robustness against various quantum noise levels, making it suitable for near-term quantum devices. Our study leverages physical inductive bias guided variational quantum algorithm, underscoring the potential of quantum computation in tackling a broad range of optimization and inverse problems. Copyright © 2025, The Authors. All rights reserved.

关键词： Inverse problems

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Towards Heisenberg limit without critical slowing down via quantum reinforcement learning

arXiv

引用

arXiv 2025年

作者： Xu, Hang Xiao, Tailong Huang, Jingzheng He, Ming Fan, Jianping Zeng, Guihua State Key Laboratory of Advanced Optical Communication Systems and Networks Institute for Quantum Sensing and Information Processing Shanghai Jiao Tong University Shanghai200240 China Hefei National Laboratory Hefei230088 China Shanghai Research Center for Quantum Sciences Shanghai201315 China AI Lab Lenovo Research Beijing100094 China

Critical ground states of quantum many-body systems have emerged as vital resources for quantum-enhanced sensing. Traditional methods to prepare these states often rely on adiabatic evolution, which may diminish the quantum sensing advantage. In this work, we propose a quantum reinforcement learning (QRL)-enhanced critical sensing protocol for quantum many-body systems with exotic phase diagrams. Starting from product states and utilizing QRL-discovered gate sequences, we explore sensing accuracy in the presence of unknown external magnetic fields, covering both local and global regimes. Our results demonstrate that QRL-learned sequences reach the finite quantum speed limit and generalize effectively across systems of arbitrary size, ensuring accuracy regardless of preparation time. This method can robustly achieve Heisenberg and super-Heisenberg limits, even in noisy environments with practical Pauli measurements. Our study highlights the efficacy of QRL in enabling precise quantum state preparation, thereby advancing scalable, high-accuracy quantum critical sensing. Copyright © 2025, The Authors. All rights reserved.

关键词： Reinforcement learning

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Hybrid Near-field and Far-field Localization with Holographic MIMO

arXiv

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arXiv 2025年

作者： Cao, Mengyuan Zhang, Haobo Eldar, Yonina C. Zhang, Hongliang State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing100871 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China Department of Mathematics and Computer Science Weizmann Institute of Science Rehovot7610001 Israel

Due to its ability to precisely control wireless beams, holographic multiple-input multiple-output (HMIMO) is expected to be a promising solution to achieve high-accuracy localization. However, as the scale of HMIMO increases to improve beam control capability, the corresponding near-field (NF) region expands, indicating that users may exist in both NF and far-field (FF) regions with different electromagnetic transmission characteristics. As a result, existing methods for pure NF or FF localization are no longer applicable. We consider a hybrid NF and FF localization scenario in this paper, where a base station (BS) locates multiple users in both NF and FF regions with the aid of a reconfigurable intelligent surface (RIS), which is a low-cost implementation of HMIMO. In such a scenario, it is difficult to locate the users and optimize the RIS phase shifts because whether the location of the user is in the NF or FF region is unknown, and the channels of different users are coupled. To tackle this challenge, we propose a RIS-enabled localization method that searches the users in both NF and FF regions and tackles the coupling issue by jointly estimating all user locations. We derive the localization error bound by considering the channel coupling and propose an RIS phase shift optimization algorithm that minimizes the derived bound. Simulations show the effectiveness of the proposed method and demonstrate the performance gain compared to pure NF and FF techniques. Copyright © 2025, The Authors. All rights reserved.

关键词： communication channels (information theory)

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Probing multi-mobility edges in quasiperiodic mosaic lattices

引用

Science Bulletin 2025年第1期70卷 58-63页

作者： Jun Gao Ivan M.Khaymovich Xiao-Wei Wang Ze-Sheng Xu Adrian Iovan Govind Krishna Jiayidaer Jieensi Andrea Cataldo Alexander V.Balatsky Val Zwiller Ali W.Elshaari Department of Applied Physics KTH Royal Institute of TechnologyAlbanova University CentreStockholm SE-10691Sweden Nordita Stockholm University and KTH Royal Institute of TechnologyStockholm SE-10691Sweden Institute for Physics of Microstructures Russian Academy of SciencesNizhny Novgorod 603950Russia Center for Integrated Quantum Information Technologies(IQIT) School of Physics and Astronomy and State Key Laboratory of Advanced Optical Communication Systems and NetworksShanghai Jiao Tong UniversityShanghai 200240China Department of Physics University of ConnecticutStorrsConnecticut 06269USA

The mobility edge(ME)is a crucial concept in understanding localization physics,marking the critical transition between extended and localized states in the energy *** localization scaling theory predicts the absence of ME in lower dimensional ***,the search for exact MEs,particularly for single particles in lower dimensions,has recently garnered significant interest in both theoretical and experimental studies,resulting in notable ***,several open questions remain,including the possibility of a single system exhibiting multiple MEs and the continual existence of extended states,even within the strong disorder ***,we provide experimental evidence to address these questions by utilizing a quasiperiodic mosaic lattice with meticulously designed nanophotonic *** observations demonstrate the coexistence of both extended and localized states in lattices with broken duality symmetry and varying modulation *** single-site injection and scanning the disorder level,we could approximately probe the ME of the modulated *** results corroborate recent theoretical predictions,introduce a new avenue for investigating ME physics,and offer inspiration for further exploration of ME physics in the quantum regime using hybrid integrated photonic devices.

关键词： Mobility edge Localization physics Mosaic lattice Nanophotonics

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