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Generative Artificial Intelligence Assisted wireless Sensing: Human Flow Detection in Practical communication Environments

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IEEE JOURNAL ON SELECTED AREAS IN communicationS 2024年第10期42卷 2737-2753页

作者： Wang, Jiacheng Du, Hongyang Niyato, Dusit Xiong, Zehui Kang, Jiawen Ai, Bo Han, Zhu Kim, Dong In Nanyang Technol Univ Coll Comp & Data Sci Singapore 639798 Singapore Singapore Univ Technol & Design Pillar Informat Syst Technol & Design Singapore 487372 Singapore Guangdong Univ Technol GDUT Sch Automat Guangzhou 510006 Peoples R China Minist Educ Key Lab Intelligent Informat Proc & Syst Integrat Guangzhou 510006 Peoples R China Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beijing Jiaotong Univ Beijing Engn Res Ctr High Speed Railway Broadband Beijing 100044 Peoples R China Univ Houston Dept Elect & Comp Engn Houston TX 77004 USA Kyung Hee Univ Dept Comp Sci & Engn Seoul 446701 South Korea Sungkyunkwan Univ Dept Elect & Comp Engn Suwon 16419 South Korea

Groundbreaking applications such as ChatGPT have heightened research interest in generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation but also signal processing, offering support for wireless sensing. Hence, we introduce a novel GAI-assisted human flow detection system (G-HFD). Rigorously, G-HFD first uses the channel state information (CSI) to estimate the velocity and acceleration of propagation path length change of the human induced reflection (HIR). Then, given the strong inference ability of the diffusion model, we propose a unified weighted conditional diffusion model (UW-CDM) to denoise the estimation results, enabling detection of the number of targets. Next, we use the CSI obtained by a uniform linear array with wavelength spacing to estimate the HIR's time of flight and direction of arrival (DoA). In this process, UW-CDM solves the problem of ambiguous DoA spectrum, ensuring accurate DoA estimation. Finally, through clustering, G-HFD determines the number of subflows and the number of targets in each subflow, i.e., the subflow size. The evaluation based on practical downlink communication signals shows G-HFD's accuracy of subflow size detection can reach 91%. This validates its effectiveness and underscores the significant potential of GAI in the context of wireless sensing.

关键词： Artificial intelligence Feature extraction Direction-of-arrival estimation wireless sensor networks wireless communication Estimation sensors Generative AI wireless sensing human flow detection

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Secure short-packet communications using a full-duplex receiver

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International Journal of Intelligent networks 2023年第1期4卷 349-354页

作者： Chen, Dechuan Li, Jin Hu, Jianwei Zhang, Xingang Zhang, Shuai College of Physics and Electronic Engineering Nanyang Normal University Nanyang473061 China Ministry of Education Nanjing210003 China National Key Laboratory for Complex Systems Simulation Beijing100101 China College of Computer Science and Technology Nanyang Normal University Nanyang473061 China

In this work, we consider the physical layer security in short-packet communications, where a full-duplex (FD) receiver receives information signals from a source while generating artificial noise (AN) to confuse an eavesdropper. Taking into account the finite blocklength coding and the self-interference (SI) in FD mode, we derive new approximation closed-form expression for the secrecy throughput. Moreover, we analyze the asymptotic secrecy throughput in two distinct scenarios, i.e., high signal-to-noise ratio (SNR) regime and infinite blocklength coding, to gain more insights. Our examination illustrates the correctness of our expressions and shows how the critical system variables affect the secrecy throughput. © 2023 The Authors

关键词： Finite difference method

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Coverage Analysis and Chance-Constrained Optimization for HSR communications With Carrier Aggregation

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IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS 2022年第9期23卷 15107-15120页

作者： Lin, Sheng-Hong Xu, Youyun Wang, Lei Wang, Jin-Yuan Nanjing Univ Posts & Telecommun Natl Local Joint Engn Res Ctr Commun & Network Te Nanjing 210003 Peoples R China Nanjing Inst Mechatron Technol Dept Automat Engn Nanjing 211135 Peoples R China Nanjing Inst Railway Technol Sch Locomot & Vehicle Nanjing 210031 Peoples R China Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Peoples R China

This paper investigates coverage analysis and performance optimization for a high-speed railway (HSR) communication system with carrier aggregation (CA). Initially, the system model is established. By using CA technology, the statistical characteristic of the received signal-to-noise ratio (SNR) is obtained. Then, for the systems with or without CA, unified theoretical expressions for the edge coverage probability (ECP) and the percentage of cell coverage area (CCA) are obtained, respectively. After that, a chance-constrained coverage optimization is proposed to improve the coverage performance, which is effectively solved by using a heuristic algorithm. Numerical results show that the derived expressions of the ECP and the percentage of CCA are accurate and can be directly used to evaluate the coverage performance without time-intensive simulations. Moreover, the impacts of CA, transmit power, cell radius, received SNR threshold, HSR scenario on coverage performance have been discussed. Furthermore, the effectiveness of the proposed coverage optimization scheme is also verified.

关键词： Computer architecture Microprocessors Optimization Rail transportation Signal to noise ratio communication systems Probability density function HSR communications cell coverage carrier aggregation ECP percentage of CCA coverage optimization

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Throughput Improvement for RIS-Empowered wireless Powered Anti-Jamming communication networks (WPAJCN)

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IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2025年 20卷 4622-4637页

作者： Chu, Zheng Chieng, David Kwong, Chiew Foong Jin, Huan Zhu, Zhengyu Huang, Chongwen Yuen, Chau Univ Nottingham Ningbo China Dept Elect & Elect Engn Next Generat Internet Everything Lab Ningbo 315100 Peoples R China Univ Nottingham Ningbo China Next Generat Internet Everything Lab Ningbo 315100 Peoples R China Univ Nottingham Ningbo China Sch Comp Sci Ningbo 315100 Peoples R China Zhengzhou Univ Sch Elect & Informat Engn Zhengzhou 450001 Peoples R China Xidian Univ State Key Lab Integrated Serv Networks Xian 710071 Peoples R China Zhejiang Univ Coll Informat Sci & Elect Engn Hangzhou 310027 Peoples R China Zhejiang Prov Key Lab Multimodal Commun Networks & Hangzhou 310027 Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore

In this paper, we propose a reconfigurable intelligent surface (RIS)-aided wireless powered anti-jamming communication network (WPAJCN), where the RIS is utilized to participate in downlink wireless power transfer (WPT), as well as uplink anti-jamming wireless information transfer (AJ-WIT). To evaluate the network anti-jamming performance, we maximize a sum anti-jamming throughput, with the constraints of downlink WPT and uplink AJ-WIT time scheduling, and unit-modulus RIS phase shifts. The formulated problem is not convex in terms of these two types of coupled variables, which cannot be directly solved. To address this problem, the Lagrange dual method and Karush-Kuhn-Tucker conditions are presented to transform its sum-of-logarithmic objective function into the logarithmically fractional counterpart, which reformulate the original problem into that with respect to RIS phase shift vectors and WPT time scheduling. Next, we propose to apply the Dinkelback algorithm to solve a non-linear fractional programming with respect to the downlink WPT and uplink AJ-WIT RIS phase shifts in an alternating fashion, each of which is derived into a semi-closed solution by utilizing the Riemannian Manifold Optimization (RMO). In addition, the optimal WPT time scheduling is obtained by numerical search. Finally, the numerical results are demonstrated to confirm the improved performance of the proposed approach compared to the benchmark counterparts, which highlights the that RIS can effectively enhance the uplink anti-jamming WIT capability as well as the downlink WPT efficiency.

关键词： Jamming Internet of Things wireless communication Reconfigurable intelligent surfaces communication system security Uplink Downlink Throughput Interference communication networks wireless powered anti-jamming communication networks (WPAJCN) reconfigurable intelligent surface (RIS) time division multiple access (TDMA) Lagrange dual method Karush-Kuhn-Tucker conditions

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Reinforcement Learning from Human-like Feedback Enhances Semantic communication with Multimodal LLMs 16

Reinforcement Learning from Human-like Feedback Enhances Sem...

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16th International Conference on wireless communications and Signal Processing, WCSP 2024

作者： Zhang, Xinyu He, Xitao Chen, Mingkai Wang, Lei Ministry of Education Nanjing University of Posts and Telecommunications Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Nanjing210003 China

ISBN: (纸本)9798350390643

Semantic communication is an emerging intelligent paradigm that provides some special solutions for the various future applications. With the rise of large language model (LLM), it may enhance well on semantic communication. However, how to balance on the accuracy and the efficiency of compression remains an urgent issue to semantic communication with LLMs. In this paper, we design a multimodal large language models (MLLMs)-enabled semantic communication system specifically designed for image transmission, where the reinforcement learning from human-like feedback (RLHLF) framework is proposed to apply reasoning and self-reflection capabilities of MLLMs to enhance the quality of semantic extraction and image generation. For one thing, we first optimize the image semantic information at the transmitter by RLHLF framework. For another thing, the generated images are optimized at the receiver by RLHLF framework. Simulation results show that our proposed system provides bandwidth savings and enables graceful performance improvement as the channel quality improves, which proves the potential of MLLMs for future semantic communication. © 2024 IEEE.

关键词： Channel coding

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Phase-matching quantum key distribution with light source monitoring

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Chinese Physics B 2022年第5期31卷 165-172页

作者： Wen-Ting Li Le Wang Wei Li Sheng-Mei Zhao Institute of Signal Processing Transmission Nanjing University of Posts and TelecommunicationsNanjing 210003China Key Laboratory of Broadband Wireless Communication and Sensor Network Technology Ministry of EducationNanjing 210003China

The transmission loss of photons during quantum key distribution(QKD)process leads to the linear key rate bound for practical QKD systems without quantum *** matching quantum key distribution(PM-QKD)protocol,an novel QKD protocol,can overcome the constraint with a measurement-device-independent structure,while it still requires the light source to be *** assumption is not guaranteed in practice,leading to practical secure *** this paper,we propose a modified PM-QKD protocol with a light source monitoring,named PM-QKD-LSM protocol,which can guarantee the security of the system under the non-ideal source *** results show that our proposed protocol performs almost the same as the ideal PM-QKD protocol even considering the imperfect factors in practical ***-LSM protocol has a better performance with source fluctuation,and it is robust in symmetric or asymmetric cases.

关键词： phase-matching quantum key distribution source fluctuation light source monitoring

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A Novel WiFi-Based Temporal Precision Detection System With Enhanced CSI Sampling

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IEEE wireless communicationS LETTERS 2025年第1期14卷 128-132页

作者： Huang, Jin Tian, Yue Hu, Xuejie Li, Zhidu Xiamen Univ Technol Fujian Key Lab Commun Network & Informat Proc Xiamen 361024 Peoples R China Chongqing Univ Posts & Telecommun Sch Commun & Informat Engn Chongqing 400065 Peoples R China

Integrated sensing and communication (ISAC) has emerged as a prominent research focus in the domains of 5G-Advanced (5G-A), 6G, and wireless fidelity (WiFi). As a passive sensing technology, WiFi-based human detection has garnered widespread attention due to its privacy, unobtrusiveness, and convenience in practical applications. This letter introduces a WiFi-based human intrusion detection system utilizing channel state information (CSI). By refining the CSI phase sampling points through the proposed sequence particle filter (SPF) CSI sampling method, the system reduces the amount of data needed for real-time sensing. A comprehensive preprocessing procedure is presented to filter out noise interference and mitigate channel fading during CSI collection. The proposed human intrusion detection algorithm accurately identifies fluctuations in the CSI phase time series, thereby determining the presence of a human and the exact moments of intrusion.

关键词： sensors wireless communication wireless fidelity Sampling methods Intrusion detection Bandwidth wireless sensor networks Real-time systems Particle filters OFDM Integrated sensing and communication channel state information WiFi human intrusion detection

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Performance analysis and parameter optimization for intelligent reflecting mirror array-aided visible light communications

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JOURNAL OF THE OPTICAL SOCIETY OF AMERICA A-OPTICS IMAGE SCIENCE AND VISION 2022年第10期39卷 1839-1848页

作者： Shi, Xiao-Di Hong, Li-Hua Yu, Peng-Fei Shi, Jia-Wei Liu, Na Wang, Jin-Yuan Nanjing Univ Posts & Telecommun Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Peoples R China

The effective deployment of an intelligent reflecting mirror array (IRMA) can enhance channel quality and improve the system performance in visible light communications (VLC) systems. This paper focuses on the performance analysis and parameter optimization of an IRMA-aided VLC system. Initially, the channel gains of both line-of-sight (LoS) link and non-LoS links are analyzed. Then, considering the blockage probability of a LoS link, a theoretical expression of the average bit error rate (ABER) is derived. To further improve the system performance, the optimization problems about the parameters of the IRMA are formulated, and schemes are proposed to solve these problems. Moreover, a kind of hardware implementation of the IRMA is provided. Numerical results verify the accuracy of the derived ABER expression and the effectiveness of the proposed schemes. (c) 2022 Optica Publishing Group

关键词： Irradiance Optical signals Pressure sensors Reflection coefficient Refractive index Visible light communications

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Intelligent multicast routing method based on multi-agent deep reinforcement learning in SDWN

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年第9期20卷 17158-17196页

作者： Hu, Hongwen Ye, Miao Zhao, Chenwei Jiang, Qiuxiang Xue, Xingsi Guilin Univ Elect Technol Sch Comp Sci & Informat Secur Guilin 541004 Peoples R China Guilin Univ Elect Technol Guangxi Key Lab Wireless Wideband Commun & Signal Guilin 541004 Peoples R China Guilin Univ Elect Technol Key Lab Cognit Radio & Informat Proc Minist Educ Guilin 541004 Peoples R China

Multicast communication technology is widely applied in wireless environments with a high device density. Traditional wireless network architectures have difficulty flexibly obtaining and maintaining global network state information and cannot quickly respond to network state changes, thus affecting the throughput, delay, and other QoS requirements of existing multicasting solutions. Therefore, this paper proposes a new multicast routing method based on multiagent deep reinforcement learning (MADRL-MR) in a software-defined wireless networking (SDWN) environment. First, SDWN technology is adopted to flexibly configure the network and obtain network state information in the form of traffic matrices representing global network links information, such as link bandwidth, delay, and packet loss rate. Second, the multicast routing problem is divided into multiple subproblems, which are solved through multiagent cooperation. To enable each agent to accurately understand the current network state and the status of multicast tree construction, the state space of each agent is designed based on the traffic and multicast tree status matrices, and the set of AP nodes in the network is used as the action space. A novel single-hop action strategy is designed, along with a reward function based on the four states that may occur during tree construction: progress, invalid, loop, and termination. Finally, a decentralized training approach is combined with transfer learning to enable each agent to quickly adapt to the dynamic changes of network link information and accelerate convergence. Simulation experiments show that MADRL-MR outperforms existing algorithms in terms of throughput, delay, packet loss rate, etc., and can establish more intelligent multicast routes. Code and model are available at https://***/GuetYe/MADRL-MR code.

关键词： software-defined wireless networking multi-agent deep reinforcement learning multicast

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UAV-Enabled Data Collection for wireless sensor networks With Distributed Beamforming

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IEEE TRANSACTIONS ON wireless communicationS 2022年第2期21卷 1347-1361页

作者： Feng, Tianxin Xie, Lifeng Yao, Jianping Xu, Jie Guangdong Univ Technol Sch Informat Engn Guangzhou 510006 Peoples R China Nanjing Univ Posts & Telecommun Minist Educ Key Lab Broadband Wireless Commun & Sensor Networ Nanjing 210003 Peoples R China Peng Cheng Lab Shenzhen 518000 Peoples R China Chinese Univ Hong Kong Shenzhen FNii Shenzhen 518172 Peoples R China Chinese Univ Hong Kong Shenzhen Sch Sci & Engn Shenzhen 518172 Peoples R China

This paper studies an unmanned aerial vehicle (UAV)-enabled wireless sensor network, in which one UAV flies in the sky to collect the data transmitted from a set of ground nodes (GNs) via distributed beamforming. We consider two scenarios with delay-tolerant and delay-sensitive applications, in which the GNs send the common/shared messages to the UAV via adaptive- and fixed-rate transmissions, respectively. For the two scenarios, we aim to maximize the average data-rate throughput and minimize the transmission outage probability, respectively, by jointly optimizing the UAV's trajectory design and the GNs' transmit power allocation over time, subject to the UAV's flight speed constraints and the GNs' individual average power constraints. However, the two formulated problems are both non-convex and thus generally difficult to be optimally solved. To tackle this issue, we first consider the relaxed problems in the ideal case with the UAV's flight speed constraints ignored, for which the well-structured optimal solutions are obtained to reveal the fundamental performance upper bounds. It is shown that for the two approximate problems, the optimal trajectory solutions have the same multi-location-hovering structure, but with different optimal power allocation strategies. Next, for the general problems with the UAV's flight speed constraints considered, we propose efficient algorithms to obtain high-quality solutions by using the techniques from convex optimization and approximation. Finally, numerical results show that our proposed designs significantly outperform other benchmark schemes, in terms of the achieved data-rate throughput and outage probability under the two scenarios. It is also observed that when the mission period becomes sufficiently long, our proposed designs approach the performance upper bounds when the UAV's flight speed constraints are ignored.

关键词： wireless communication Trajectory wireless sensor networks Resource management Array signal processing Data collection Throughput Unmanned aerial vehicle (UAV) distributed beamforming throughput maximization outage minimization trajectory design power allocation

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