Article
Telecommunications
Maroua Taghouti, Tobias Waurick, Mate Toemoeskoezi, Anil K. Chorppath, Frank H. P. Fitzek
Summary: The paper examines the impact of compressed sensing on network coding to enable one-step decoding for the reconstruction of compressed data. By using normalized coefficient matrices from Gaussian distributions, higher efficiency and scalability are achieved, particularly in multi-hop networks where the recoding feature of network coding can be exploited.
TRANSACTIONS ON EMERGING TELECOMMUNICATIONS TECHNOLOGIES
(2021)
Article
Engineering, Electrical & Electronic
Pengcheng Wei, Fangcheng He
Summary: This study combines compressed sensing technology with wireless networks to expand compression algorithms spatially, improving data processing capabilities and accuracy.
IEEE SENSORS JOURNAL
(2021)
Article
Optics
Wang Hao-quan, Tang Qian-nan, Ren Shi-lei
Summary: This paper investigates distributed video coding based on compressed sensing theory, using the discriminative K-SVD algorithm. Experimental results demonstrate that the proposed method achieves better reconstruction results and saves a significant amount of computing time.
Review
Neurosciences
Biao Sun, Wenfeng Zhao
Summary: This article provides a comprehensive survey of literature on compressed sensing of neurophysiology signals, discussing its applications, technical challenges, and prospects in neural signal transmission.
FRONTIERS IN NEUROSCIENCE
(2021)
Article
Computer Science, Information Systems
Siwang Zhou, Yi Lian, Daibo Liu, Hongbo Jiang, Yonghe Liu, Keqin Li
Summary: This article addresses the decentralized storage problem in mobile crowdsensing systems and proposes a compressive distributed storage scheme based on compressive sensing. By encoding the sensing data in the local trajectories of participants and exploiting inter-period correlations, the entire information of the area can be stored and recovered with improved accuracy.
ACM TRANSACTIONS ON SENSOR NETWORKS
(2022)
Article
Physics, Multidisciplinary
Hanqi Tang, Ruobin Zheng, Zongpeng Li, Keping Long, Qifu Sun
Summary: This study proposes a novel scalable random linear network coding (RLNC) framework based on embedded fields to address the existence of heterogeneous devices in complex network environments. The research findings demonstrate that this framework outperforms traditional methods in terms of decoding compatibility and decoding performance, and is able to adapt to the sparsity of received binary coding vectors.
Article
Computer Science, Information Systems
Nan Cen, Zhangyu Guan, Tommaso Melodia
Summary: In this paper, a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN is proposed. The architecture leverages the properties of Compressed Sensing (CS) to overcome the limitations of traditional encoding techniques and can transmit multi-view streams with guaranteed video quality at lower power consumption.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2022)
Article
Engineering, Electrical & Electronic
R. Monika, Samiappan Dhanalakshmi, R. Kumar, R. Narayanamoorthi
Summary: Underwater Wireless Sensor Networks (UWSNs) are used for data collection and processing of underwater targets and resources. To save energy and improve the sensor's lifetime, a new image compression method called Coefficient Permuted Adaptive Block Compressed Sensing (CP-ABCS) is proposed. This method reduces data volume by permuting coefficients and adopting adaptive block compressed sensing, achieving better image reconstruction with fewer samples.
IEEE SENSORS JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Weizhi Lu, Mingrui Chen, Kai Guo, Weiyu Li
Summary: For deep networks with complex nonlinearity, this paper proposes understanding and constructing them as a cascade of compressed sensing. Each compressed sensing module consists of two layers, which correspond to the two data transforms involved in compressed sensing. The proposed construction has the advantages of being analyzable with compressed sensing theory and enabling layerwise learning via back-propagating the target.
IEEE SIGNAL PROCESSING LETTERS
(2023)
Article
Mathematics, Interdisciplinary Applications
Jiexiang Wang, Keli Fu, Yu Gu, Tao Li
Summary: This paper studies distributed convex optimization over a multi-agent system using a distributed gradient-tracking algorithm. By imposing constraints on conditional graphs, global cost function, and step sizes, the authors prove that the algorithm can converge to the optimal solution at a geometric rate.
JOURNAL OF SYSTEMS SCIENCE & COMPLEXITY
(2021)
Article
Physics, Multidisciplinary
Dipa Saha, Sayantan Mitra, Bishnu Bhowmik, Ankur Sensharma
Summary: A novel model of random geometric graph, IRGG, with circular boundary shape and an empty concentric region inside the network has been developed and studied in details. The second difference in IRGG, allowing communicating edges to pass through the empty region, leads to significant alterations in physically relevant network properties. Analytical expressions for these features have been provided and are in good agreement with simulation results.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Computer Science, Information Systems
Mustafa Tosun, Umut Can Cabuk, Elif Haytaoglu, Orhan Dagdeviren, Yusuf Ozturk
Summary: Random geometric graphs can be used for constructing topology formations in wireless ad-hoc networks (WANETs). They are beneficial for energy-saving schemes where a randomly alternating subset of deployed nodes is temporarily turned off. This also enhances network security by periodically rerouting the data flow.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Multidisciplinary
Yishun Liu, Keke Huang, Chunhua Yang, Zhen Wang
Summary: Currently, the network model is a common framework for representing complex systems, and its structure is essential for controlling and applying networked systems. With the advent of the Big Data era, the scale of network structures is expanding rapidly. However, traditional centralized reconstruction methods are not practical due to the high computing resource requirements. To address this challenge, a distributed local reconstruction method is proposed for unweighted networks. By introducing the ADMM method, the complex reconstruction problem is decomposed into multiple subproblems, reducing the need for computing resources. In addition, a binary constraint is introduced to ensure reconstruction accuracy based on network structure characteristics. Extensive experiments demonstrate the superiority of the proposed method in reconstructing networks of different scales and types with limited computing resources, as well as its accuracy and robustness against noise.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Engineering, Electrical & Electronic
Faeze Heydaryan, Jie Luo
Summary: The paper introduces a distributed MAC framework to support hierarchical user groups in a random multiple access system. It ensures channel availability above a pre-determined threshold when the number of primary users is small and drives transmission probabilities of secondary users to zero when the number of primary users is large, without rejecting channel access to primary users.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2021)
Article
Anthropology
Jan Schulz, Daniel M. Mayerhoffer, Anna Gebhard
Summary: Individual citizens across income groups and countries have significantly incorrect perceptions of economic inequality. These misperceptions can have significant consequences, as they may shape redistributive preferences based on perceived inequality rather than actual inequality. Our proposed explanation of perceived inequality, based on network-based theories, can replicate all observed stylised facts and generate social networks similar to real-world networks.
Article
Engineering, Electrical & Electronic
Nguyen Quang Hieu, Diep N. Nguyen, Dinh Thai Hoang, Eryk Dutkiewicz
Summary: RSMA-based multicast approach can address the computational demands and dynamic user needs in virtual reality streaming applications, achieving millisecond-latency requirement.
IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Cong T. T. Nguyen, Dinh Thai Hoang, Diep N. N. Nguyen, Yong Xiao, Hoang-Anh Pham, Eryk Dutkiewicz, Nguyen Huynh Tuong
Summary: In this article, the authors propose FedChain, a novel framework for effective token transfer between different blockchain networks. They introduce a federated-blockchain system and a cross-chain transfer protocol to facilitate secure and decentralized transfer of tokens. They also develop a PoS-based consensus mechanism for FedChain that satisfies strict security requirements and achieves better performance. Furthermore, they address the problem of centralization in the FedChain system with a Stackelberg game model, proving the uniqueness of the equilibrium and finding the exact formula. The results are important for stakeholders to determine investment strategies and for chain operators to maximize benefits and security protection. Simulation results demonstrate the effectiveness of the FedChain framework in maximizing profits and enhancing security and performance.
IEEE TRANSACTIONS ON SERVICES COMPUTING
(2023)
Article
Automation & Control Systems
Ly Vu, Quang Uy Nguyen, N. Diep Nguyen, Dinh Thai Hoang, Eryk Dutkiewicz
Summary: This article proposes a novel solution to enable robust cloud IDSs using deep neural networks. By developing two deep generative models to synthesize malicious samples on the cloud systems, the accuracy of cloud IDSs is significantly improved. The experiments also show that this method enhances the accuracy of detecting DDoS attacks.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Chemistry, Analytical
Junwen Deng, Hang Li, Jian Andrew Zhang, Xiaojing Huang, Zhiqun Cheng
Summary: The performance of mmWave LOS MIMO systems using hybrid arrays of planar subarrays was studied. The achievable maximum spatial multiplexing gain was characterized by spectral efficiency and EDoF. Analytical expressions for optimal design parameters in the analog domain were derived, and eigenvalue expressions for the equivalent LOS MIMO channel matrix were provided. Numerical and simulation results showed the superiority of planar subarrays over traditional arrays in terms of spectral efficiency and EDoF in Ricean fading channels.
Article
Computer Science, Information Systems
Kai Wu, J. Andrew Zhang, Xiaojing Huang, Y. Jay Guo
Summary: This article proposes a joint communication and radio sensing scheme based on orthogonal time-frequency space (OTFS) waveform (JCAS). By designing a series of echo preprocessing methods and optimizing key parameters, effective sensing on OTFS is achieved. The extensive simulations show that the proposed sensing method performs well in estimation accuracy of target parameters and adapts to a wide range of system parameters, with low complexity dominated by a 2-D Fourier transform.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Cong T. Nguyen, Diep N. Nguyen, Dinh Thai Hoang, Khoa Tran Phan, Dusit Niyato, Hoang-Anh Pham, Eryk Dutkiewicz
Summary: Coded distributed computing (CDC) is a promising solution to address the straggling effects in conventional distributed computing systems, by assigning redundant workloads to computing nodes to enhance system performance. However, CDC may lead to wasteful energy consumption at edge nodes. In this work, we propose a framework called CERA, which includes two stages: a linearization approach and hybrid algorithm to minimize processing time, and an online approach based on Lyapunov optimization to reduce energy consumption without affecting processing time.
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
(2023)
Article
Computer Science, Information Systems
Baoling Shan, Xin Yuan, Wei Ni, Xin Wang, Ren Ping Liu, Eryk Dutkiewicz
Summary: This article introduces a new graph-learning technique for accurately inferring the graph structure of COVID-19 data. By estimating the graph Laplacian and using centrality measures, the method identifies influential countries for pandemic response analysis. The accuracy of the technique is validated and it outperforms existing techniques in terms of root mean squared error and correlation of determination. The identified influential countries are expected to contribute to the study of COVID-19 spread.
IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS
(2023)
Article
Computer Science, Information Systems
Tran Viet Khoa, Dinh Thai Hoang, Nguyen Linh Trung, Cong T. Nguyen, Tran Thi Thuy Quynh, Diep N. Nguyen, Nguyen Viet Ha, Eryk Dutkiewicz
Summary: Federated learning is an effective approach for cyberattack detection systems in IoT networks, which can improve learning efficiency, reduce overheads, and enhance privacy. However, the challenge lies in the unavailability of labeled data and dissimilarity in data features. This article proposes a collaborative learning framework that leverages transfer learning to overcome these challenges.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Computer Science, Information Systems
Nam Hoai Chu, Diep N. Nguyen, Dinh Thai Hoang, Quoc-Viet Pham, Khoa Tran Phan, Won-Joo Hwang, Eryk Dutkiewicz
Summary: Integrated communications and sensing is an important technology for IoT applications. This article proposes a novel framework for autonomous vehicles, which optimizes the waveform structure using deep reinforcement learning and Markov decision process. The proposed approach can adaptively optimize the waveform structure to improve sensing and data communication performance.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Engineering, Electrical & Electronic
Le Chung Tran, Anh Tuyen Le, Xiaojing Huang, Eryk Dutkiewicz, Duy Ngo, Attaphongse Taparugssanagorn
Summary: This paper introduces a new hybrid TOA/AOA localization algorithm called T1Aa, which reduces power consumption by reducing agent complexity, and demonstrates that the algorithm performs similarly to conventional methods in experiments.
IEEE SENSORS LETTERS
(2023)
Article
Engineering, Electrical & Electronic
Ali Raza, Rasool Keshavarz, Eryk Dutkiewicz, Negin Shariati
Summary: This article presents a compact multiservice antenna (MSA) that uses a reconfigurable complementary spiral resonator for sensing and communication. The proposed structure operates in three modes and can switch between dual-band joint communication and sensing, dual-band, and single-band operation. The antenna's sensing ability is utilized to measure soil moisture using frequency-domain reflectometry (FDR).
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Computer Science, Theory & Methods
Baoling Shan, Xin Yuan, Wei Ni, Xin Wang, Ren Ping Liu, Eryk Dutkiewicz
Summary: This paper presents a novel approach to obfuscating latent graph structure and stimuli, aiming to balance privacy protection and data utility. By analyzing the graph Fourier transform basis and latent stimuli, the authors successfully perturb the latent information. Experimental results demonstrate the superiority of their approach over differential privacy-based methods in graph inference attacks.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Article
Computer Science, Information Systems
Yuris Mulya Saputra, Diep N. Nguyen, Dinh Thai Hoang, Quoc-Viet Pham, Eryk Dutkiewicz, Won-Joo Hwang
Summary: This article proposes a novel framework to address straggling and privacy issues in federated learning-based mobile application services. It takes into account limited computing/communications resources, privacy cost, rationality, and incentive competition among participating entities. The framework utilizes information provided by mobile users to determine the best participants and includes methods to mitigate straggling problems and protect privacy. Experimental results show significant improvements in training time, prediction accuracy, and network welfare compared to baseline methods.
IEEE TRANSACTIONS ON MOBILE COMPUTING
(2023)
Article
Computer Science, Theory & Methods
H. D. Tuan, Ali A. A. Nasir, Y. Chen, E. Dutkiewicz, H. V. Poor
Summary: This paper focuses on a network scenario where a multi-antenna access point serves multiple single-antenna users in the presence of multiple eavesdroppers, with the aid of a reconfigurable intelligent surface (RIS). The RIS employs low-resolution programmable reflecting elements (PREs) for cost-effective implementation. In order to establish secure links for all users, we consider the joint design of the transmit beamformers and PREs to maximize either the geometric mean of secrecy rates or the worst user's secrecy rate. Novel computational algorithms of low computational complexity are developed for the solution of these mixed discrete continuous optimization problems. Simulations show the merit of the proposed designs in achieving fair secrecy rate distributions and ensuring secure links for all users.
IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY
(2023)
Proceedings Paper
Computer Science, Hardware & Architecture
Nguyen Van Huynh, Nguyen Quang Hieu, Nam H. Chu, Diep N. Nguyen, Dinh Thai Hoang, Eryk Dutkiewicz
Summary: This work proposes a novel anti-eavesdropping solution that utilizes ambient backscatter technology to transmit secret information without requiring extra power or computing resources.
2023 IEEE WIRELESS COMMUNICATIONS AND NETWORKING CONFERENCE, WCNC
(2023)
