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Secure Integrated Sensing and SWIPT via Active IRS

IEEE Transactions on Wireless Communications 2025年

作者： Xu, Jinlei Zhang, Jifa Liu, Mingqian Zhao, Nan Al-Dhahir, Naofal Wang, Xianbin Dalian University of Technology School of Information and Communication Engineering Dalian116024 China Xidian University State Key Laboratory of Integrated Service Networks Shanxi Xian710071 China University of Texas at Dallas Department of Electrical and Computer Engineering RichardsonTX75083 United States Western University Department of Electrical and Computer Engineering LondonONN6A 5B9 Canada

To achieve sustainable communication and sensing, simultaneous wireless information and power transfer (SWIPT) has been introduced into integrated sensing and communication (ISAC). However, this combination brings significant security challenges due to signal multiplexing and spectrum sharing. In this paper, an active intelligent reflecting surface (IRS) assisted secure integrated sensing and SWIPT system is proposed with the power splitting (PS) model adopted. To maximize the harvested power while satisfying the constraints of sidelobe level ratio and secrecy rate, a problem is formulated to jointly optimize the transmit beamforming, artificial noise (AN) vectors, PS ratios, and amplification factors and phase shifts of active IRS, which is difficult to solve due to the coupled variables. To this end, we decompose it into two sub-problems, and propose two alternating optimization (AO) algorithms to solve them. First, an AO algorithm based on semi-definite relaxation (SDR) is developed. Specifically, we develop a two-layer algorithm to obtain the transmit beamforming matrix, AN covariance matrix and PS ratios, and utilize the penalty-based method to design the coefficients of active IRS. To reduce the complexity caused by the high-dimensional matrix operation of SDR, an AO algorithm based on successive convex approximation (SCA) is proposed, which can approximate the original problem as a sequence of convex counterparts via the first-order Taylor expansion. Simulation results show that the SCA-based AO algorithm can achieve the performance close to that of SDR with lower complexity. © 2002-2012 IEEE.

关键词： Inductive power transmission

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P2C2T: Preserving the Privacy of Cross-Chain Transfer

P2C2T: Preserving the Privacy of Cross-Chain Transfer

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IEEE Symposium on Security and Privacy

作者： Panpan Han Zheng Yan Laurence T. Yang Elisa Bertino The State Key Laboratory on Integrated Services Networks School of Cyber Engineering Xidian University China Hangzhou Institute of Technology Xidian University China School of Computer Science and Artificial Intelligence Zhengrhou University China Department of Computer Science Purdue University USA

ISBN: (数字)9798331522360

ISBN: (纸本)9798331522377

Blockchain-enabled digital currency systems have typically operated in isolation, lacking necessary mechanisms for seamless interconnection. Consequently, transferring assets across distinct currency systems remains a complex challenge, with existing schemes often falling short in ensuring security, privacy, and practicality. This paper proposes P2C2T - a privacy-preserving cross-chain transfer scheme. It is the first scheme to address atomicity, unlinkability, indistinguishability, non-collateralization, and required functionalities across diverse currency systems. P2C2T is based on threshold anonymous atomic locks (TA 2 L), also proposed by us, serving as the cornerstone for guaranteeing atomic cross-chain transfer while obscuring the payment relationships between users. By combining TA 2 L with verifiable timed discrete logarithm schemes, P2C2T renders cross-chain transactions indistinguishable from regular intra-chain ones. Notably, P2C2T eliminates the collateralization of senders and imposes minimal requirements on underlying blockchains, specifically on the ability to verify signatures. We substantiate the security of TA 2 L based on a proposed cryptographic notion called threshold blind conditional signatures and demonstrate the security of P2C2T through necessary proofs. Additionally, we compare the performance of P2C2T with an existing scheme that has properties closest to P2C2T. The comparison reveals that P2C2T reduces overhead by at least 85.488% in terms of running time, communication cost, and storage cost when completing a cross-chain transfer. We further conduct cross-chain transfers and intra-chain payments using the Bitcoin testnet and Litecoin testnet to illustrate the privacy and practicality of P2C2T.

关键词： Privacy Costs Protocols Online banking Bitcoin Minimization Blockchains Synchronization Currencies

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ARTIFICIAL INTELLIGENCE(AI)-DRIVEN SPECTRUM MANAGEMENT

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China Communications 2020年第2期17卷 I0001-I0003页

作者： Zan Li Zhiguo Ding Jia Shi Walid Saad Lie-Liang Yang the State Key Laboratory of Integrated Services Networks(ISN) School of Telecommunications EngineeringXidian University 不详 the State Key Laboratory of Integrated Services Networks(ISN) the Department of Electrical and Computer Engineering at Virginia Tech

Recent advances in communication and networking technologies are leading to a plethora of novel wireless services that range from unmanned aerial vehicle(UAV)communication to smart cognitive networks and massive Internet of Things(IoT)*** these emerging applications over the fifth generation(5G)of wireless cellular systems requires meeting numerous challenges pertaining to spectrum sharing and *** fact,most 5G applications will be highly reliant on intelligent spectrum management techniques,which should adapt to dynamic network environments while also guaranteeing high reliability and high quality-of-experience(QoE).

关键词： IoT spectrum guarantee

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Enhancing Analysis by Integrating Link and Node Metrics based Fuzzy Logic for IoT System

Enhancing Analysis by Integrating Link and Node Metrics base...

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Embedded Systems and Artificial Intelligence (ESAI), International Conference on

作者： Soukayna Riffi Boualam Mariyam Ouaissa Mariya Ouaissa Abdellatif Ezzouhairi Computer Networks and Systems Laboratory Faculty of Sciences Moulay Ismail University Meknes Morocco Laboratory of Information Technologies Chouaib Doukkali University El Jadida Morocco Computer Systems Engineering Laboratory Cadi Ayyad University Marrakech Morocco National School of Applied Sciences Sidi Mohammed Ben Abdellah University Fez Morocco

ISBN: (数字)9798331522056

ISBN: (纸本)9798331522063

The Internet of Things (IoT) has recently emerged as a transformative paradigm driven by technological advancements. networks comprised of connected devices face numerous challenges, particularly in facilitating communication among these devices. These challenges arise due to the inherent constraints of IoT, such as limited power and the nature of Low Power and Lossy networks (LLNs). LLNs require an efficient routing protocol that can cater to the needs of diverse applications while managing these constraints effectively. Over the past few years, The IETF ROLL (Routing Over Low Power and Lossy networks) working group has developed a new routing protocol, RPL (IPv6 Routing Protocol for LLNs). RPL leverages objective functions to construct and optimize routing paths to ensure efficient data transmission within LLNs. Nevertheless, the IETF ROLL group did not specify the exact number or types of metrics to be employed in these objective functions, leaving room for customization based on specific application requirements. This study delves into the RPL routing protocol, examining its structure and functionality. Furthermore, we propose a novel objective function that integrates multiple metrics to enhance routing performance. The integration of these metrics is accomplished through fuzzy logic, enabling a more flexible and nuanced approach to decision-making in the routing process. This method aims to improve the overall efficiency and reliability of data transmission within LLNs, addressing the unique challenges posed by IoT environments.

关键词： Measurement Fuzzy logic Energy consumption Linear programming Routing Routing protocols Stability analysis Data communication Internet of Things Standards

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Multi-Channel Hypergraph Convolution Group Recommendation with Member Information Enhancement 25

Multi-Channel Hypergraph Convolution Group Recommendation wi...

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25th IEEE International Conferences on High Performance Computing and Communications, 9th International Conference on Data Science and Systems, 21st IEEE International Conference on Smart City and 9th IEEE International Conference on Dependability in Sensor, Cloud and Big Data Systems and Applications, HPCC/DSS/SmartCity/DependSys 2023

作者： Chen, Tianhao Gao, Qian Fan, Jun Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Shandong Jinan250014 China Qilu University of Technology Shandong Academy of Sciences Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Shandong Jinan250353 China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Shandong Jinan250014 China China Telecom Digital Intelligence Techonology Co Ltd Shandong Jinan250101 China

ISBN: (纸本)9798350330014

Group recommendation involves comprehensively considering various aspects, including members and items, to predict the overall interests of a group and recommend suitable items through a recommendation system. With the rapid evolution of the Internet, online group activities have become increasingly prevalent, making group recommendation a highly discussed topic within the realm of recommendation systems. However, current research in group recommendation still confronts the following challenges. Firstly, a predominant portion of group recommendation research focuses solely on aggregating group-level information, neglecting the valuable contribution of higher-order member-level insights to group recommendation. Moreover, some aggregation strategies overly prioritize fairness, thereby disregarding common real-world patterns. Secondly, previous studies have primarily relied on aggregating individual member interests to establish group preferences, lacking a holistic consideration of group dynamics. To tackle these challenges, this study introduces an innovative approach by implementing multi-channel hypergraph convolution within the member perspective. This approach aims to effectively extract higher-order insights from members by utilizing a member information enhancement module. By establishing group interconnections based on similarity and employing an adaptive fusion network to amalgamate multiple viewpoints, a final representation is derived. Experimental results demonstrate that our proposed model surpasses baseline models by 3% to 4% in terms of hit rate and accuracy, validating the efficacy of our approach. © 2023 IEEE.

关键词： Recommender systems

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Social-enhanced recommendation using graph-based contrastive learning 25

Social-enhanced recommendation using graph-based contrastive...

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作者： Xue, Peng Gao, Qian Fan, Jun Qilu University of Technology Shandong Academy of Sciences Key Laboratory of Computing Power Network and Information Security Ministry of Education Shandong Computer Science Center Shandong Jinan250014 China Qilu University of Technology Shandong Academy of Sciences Shandong Engineering Research Center of Big Data Applied Technology Faculty of Computer Science and Technology Shandong Jinan250353 China Shandong Provincial Key Laboratory of Computer Networks Shandong Fundamental Research Center for Computer Science Shandong Jinan250014 China China Telecom Digital Intelligence Techonology Co Ltd Shandong Jinan250101 China

ISBN: (纸本)9798350330014

The social network-based recommendation model use social network information to mitigate data sparsity issues and improve the accuracy of recommendation models. However, In most social network-based recommendation algorithms, the social neighbors' contributions are difficult to distinguish from the central user's, neglecting hidden correlations in social infor-mation. In order to solve this problem, this paper presents a graph-based contrastive learning framework for social-enhanced recommendation (SoGCLR) that utilizes implicit social information captured by a new social relation attention mechanism, en-rich user representations, and improve model robustness through graph-based contrastive learning. Specifically, the paper captures the degree of contribution of each neighbor in the social graph to the central user through a social relation attention layer, thus obtaining hidden correlations in social information, and further integrates this with user information in the user-item interaction graph to enrich user representations. In addition, the paper incorporates graph-based contrastive learning into the recommendation task using cross-layer contrastive learning, calculating contrastive loss and mapping nodes with similar but different exposure rates to nearby regions to mitigate exposure bias issues. Results from Ciao and Epinions demonstrate that SoGCLR reduces RMSE and MAE by 1.33% to 1.84% compared with baseline models. © 2023 IEEE.

关键词： Recommender systems

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Towards an intelligent photonic system

引用

Science China(Information Sciences) 2020年第6期63卷 80-96页

作者： Weiwen ZOU Bowen MA Shaofu XU Xiuting ZOU Xingjun WANG State Key Laboratory of Advanced Optical Communication Systems and Networks Intelligent Microwave Lightwave Integration Innovation Center (iMLic) Department of Electronic EngineeringShanghai Jiao Tong University State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Engineering and Computer Science Peking University

The emerging intelligence technologies represented by deep learning have broadened their applications to various fields. Beyond the conventional electronics-based processing systems, the convergence of photonics and artificial intelligence(AI) technology enhances the performance and learning ability of AI. In this review, we propose the concept of an intelligent photonic system(IPS), illustrating it as a developing architecture with three different versions. For each version of IPS, we review several representative *** we discuss the challenges towards an IPS and provide some prospects for the future development.

关键词： intelligent photonic system deep learning artificial intelligence optical neural network neuromorphic photonics

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A Note on "Constructing Bent Functions Outside the Maiorana-McFarland Class Using a General Form of Rothaus"

arXiv

引用

arXiv 2025年

作者： Guo, Fei Wang, Zilong Gong, Guang State Key Laboratory of Mathematical Engineering and Advanced Computing Information Engineering University Zhengzhou450001 China State Key Laboratory of Integrated Service Networks Xidian University Xi’an710071 China Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada

In 2017, Zhang et al. proposed a question (not open problem) and two open problems in [IEEE TIT 63 (8): 5336–5349, 2017] about constructing bent functions by using Rothaus’ construction. In this note, we prove that the sufficient conditions of Rothaus’ construction are also necessary, which answers their question. Besides, we demonstrate that the second open problem, which considers the iterative method of constructing bent functions by using Rothaus’ construction, has only a trivial solution. It indicates that all bent functions obtained by using Rothaus’ construction iteratively can be generated from the direct sum of an initial bent function and a quadratic bent function. This directly means that Zhang et al.’s construction idea makes no contribution to the construction of bent functions. To compensate the weakness of their work, we propose an iterative construction of bent functions by using a secondary construction in [DCC 88: 2007–2035, 2020]. © 2025, CC BY-NC-ND.

关键词： Hadamard transforms

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Meta-Critic Reinforcement Learning for IOS-Assisted Multi-User Communications in Dynamic Environments

Meta-Critic Reinforcement Learning for IOS-Assisted Multi-Us...

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IEEE Conference on Vehicular Technology (VTC)

作者： Qinpei Luo Boya Di Zhu Han State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Electrical and Computer Engineering Department University of Houston TX USA

Capable of reflecting and refracting the incident signals on both sides simultaneously, the intelligent omnidirectional surface (IOS) has recently been proposed as a promising solution to enhance the capacity of wireless networks. However, the large number of IOS elements brings a heavy burden to the beamforming scheme design, especially for applications that require a fast response to varying environments. In this paper, aiming to maximize the sum rate of an IOS-aided multi-user system via IOS-enabled beamforming design that can rapidly adapt to dynamic channel states and user mobility, we develop a novel meta-critic reinforcement learning framework where a meta-critic network recognizes the environment change and automatically re-trains of the learning model. A stochastic Explore and Reload procedure is tailored to reduce the high-dimensional action space problem. Simulation results show the proposed scheme can converge to a higher sum rate more rapidly compared to the benchmark methods in dynamic settings. The robustness of our scheme against different IOS sizes is also verified.

关键词：

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Near-Far Field Three-Stage Beam Training for RIS-Assisted Wideband OFDM Communications

Near-Far Field Three-Stage Beam Training for RIS-Assisted Wi...

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IEEE Conference on Wireless Communications and Networking

作者： Zhichao Cheng Shupei Zhang Shu Fu Boya Di School of Electronics Engineering and Computer Science Peking University Beijing China State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Microelectronics and Communication Engineering Chongqing University Chongqing China

ISBN: (数字)9798350368369

ISBN: (纸本)9798350368376

Large-scale reconfigurable intelligent surfaces (RISs) have emerged as a promising technology for signal strength enhancement and coverage extension in 6G networks. However, as the antenna scale and the bandwidth increase, large-scale RIS-assisted wideband orthogonal frequency division multiplexing (OFDM) communication systems face new challenges due to the near-field range expansion and the beam split effect, complicating the acquisition of channel state information (CSI). To tackle these challenges, in this paper, we present a wideband beam training scheme by utilizing the beam split effect to bypass the CSI acquisition. Specifically, by analyzing the beam split effect in RIS-assisted OFDM communication systems, we propose a beam-split-aware codebook capable of covering both the near and far fields. The coverage of codewords in the proposed codebook is expanded benefiting from the beam split effect, leading to fewer codewords compared to conventional narrow-band codebooks. Utilizing such a codebook, a three-stage beam training mechanism is performed to obtain the optimal codeword with low time overhead, thereby facilitating the beamforming. Simulation results demonstrate that the proposed scheme outperforms existing codebook-based beam training schemes in terms of training overhead and sum rate in the hybrid near-far field.

关键词： Training Upper bound Array signal processing OFDM Simulation Reconfigurable intelligent surfaces Broadband antennas Wideband Faces Channel state information

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