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2023 IEEE MTT-S International Wireless Symposium, IWS 2023

作者： Qi, Huanhuan Liu, Haiwen Huang, Mo School of Information and Communications Engineering Xi' An Jiaotong University Xi'an China Faculty of Science and Technology State Key Laboratory of Analog and Mixed-Signal Vlsi China Institute of Microelectronics University of Macau Department of Electrical and Computer Engineering China

ISBN: (纸本)9798350336535

In this paper, a novel filtering balun based on microstrip-to-slotline transition is proposed. Utilizing the inherent out-of-phase electric field distributions on the adjacent grounds of slotline, the balun function is realized. In order to realize the wide notched-band and stopband performance for radio astronomical applications, spoof surface plasmon polariton (SSPP) metamaterial and multi-mode hairpin ring resonators (HRRs) are adopted. With these novel structures loaded, the proposed filtering balun exhibits a wide band from 1GHz to 6 GHz. The notched band is from 3.2 GHz to 4.4 GHz, within the notched band, the rejection level is better than 15 dB. Besides, the out-of-band suppression is below 35 dB in the wide frequency range from 6 GHz to 8 GHz. © 2023 IEEE.

关键词： Metamaterials

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Reliable NR-V2X Broadcast Transmission by Relay

Reliable NR-V2X Broadcast Transmission by Relay

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IEEE Conference on Vehicular Technology (VTC)

作者： Suhua Tang Sadao Obana Department of Computer and Network Engineering The University of Electro-Communications Tokyo Japan The University of Electro-Communications Tokyo Japan

Vehicular communication plays an important role in cooperative perception. 3GPP has successively standardized LTE-V2X and NR-V2X to support different kinds of vehicular communications, especially local information dissemination among vehicles by broadcast. There is no feedback for broadcast transmission. Therefore, blind retransmission usually is used to improve system reliability. But its effect is limited in the non-line-of-sight (NLOS) scenario. In this paper, with NR-V2X mode 2 as an example, we study how to improve the reliability of local broadcast transmission by using relay, from two aspects. (i) A vehicle allocates resources for the retransmissions at a relay vehicle in advance to reduce the delay. (ii) A relay vehicle is selected to help multiple vehicles simultaneously, considering the link quality between vehicles. Simulation evaluations confirm that using relay helps to improve information dissemination at the NLOS intersections, even when there is no vehicle at the intersection center.

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RadYOLOLet: Radar Detection and Parameter Estimation Using YOLO and WaveLet

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IEEE Transactions on Cognitive communications and Networking 2024年

作者： Sarkar, Shamik Guo, Dongning Cabric, Danijela Indraprastha Institute of Information Technology Electronics and Communications Engineering Department Delhi110020 India Northwestern University Electrical and Computer Engineering Department EvanstonIL60208 United States University of California at Los Angeles Electrical and Computer Engineering Department Los AngelesCA90095 United States

In emerging and future shared-spectrum wireless networks like Citizens Broadband Radio Service (CBRS), the ability to detect radar signals without assistance from the radar transmitter is of paramount importance. This paper presents RadYOLOLet, a novel supervised deep learning-based spectrum sensing approach designed to detect low-power radar signals in the presence of interference and estimate the radar signal parameters. RadYOLOLet employs two independently trained convolutional neural networks, RadYOLO and Wavelet-CNN. RadYOLO operates on spectrograms and provides most of the capabilities of RadYOLOLet unless the signal-to-noise-and-interference ratio (SINR) is very low. In such cases, Wavelet-CNN is utilized to operate on the continuous wavelet transform of the captured signals, enhancing the detection outcome. The performance of RadYOLOLet is evaluated through various experiments using different types of interference signals. The results indicate that RadYOLOLet maintains accurate radar detection performance for SINRs of 16 dB or higher for all five types of radar signals considered, which surpasses the capabilities of other comparable methods. © 2024 IEEE.

关键词： Signal to noise ratio

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Solution of the Problem of Positioning Moving Objects on Analytical Trajectories With a Minimum Composition of Satellite Measurements

Solution of the Problem of Positioning Moving Objects on Ana...

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International Conference on Industrial engineering, Applications and Manufacturing (ICIEAM)

作者： Sergey V. Sokolov Daniil V. Marshakov Irina V. Reshetnikova Department of Informatics and Computer Engineering Moscow Technical University of Communications and Informatics Rostov-on-Don Russia Research Department Moscow Technical University of Communications and Informatics Rostov-on-Don Russia

ISBN: (数字)9798331512194

ISBN: (纸本)9798331512200

The paper deals with the problem of high-precision positioning for mobile objects moving along program trajectories. An equation describing the dynamics of changing the spatial coordinates of the object based only on satellite measurements and invariant to its physical and technical characteristics is obtained. In addition, an equation of the spatial coordinates observer, also invariant to the design features of the object, is constructed on the basis of primary pseudodistance measurements. The peculiarity of application of this approach in the considered case is its complementation with the idea of approximation of a priori (programmed) trajectory of a mobile object by a set of trajectory intervals described by the given analytical models in the object coordinate space. As such trajectory intervals, the paper considers orthodromic (shortest) and circular intervals, which are the most typical for programme trajectories of transport objects (highways, railways, airlines, etc.). Analytical dependences of spatial coordinates are obtained for circular intervals. Since approximation by the specified trajectory intervals can be easily implemented using electronic maps, in general, the integration of electronic map information and nonlinear filtering algorithms in the processing of primary satellite measurements makes it possible to drastically reduce computational costs when estimating the current coordinates of a mobile object while significantly improving positioning accuracy compared to traditional methods of processing satellite messages. The effectiveness of the proposed approach is illustrated by a numerical example.

关键词： Satellites Coordinate measuring machines Accuracy Filtering Current measurement Position measurement Stability analysis Mathematical models Trajectory Numerical stability

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Toward interoperable representation and sharing of disinformation incidents in cyber threat intelligence

arXiv

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arXiv 2025年

作者： González, Felipe Sánchez Pastor-Galindo, Javier Ruipérez-Valiente, José A. Department of Information and Communications Engineering University of Murcia 30100 Spain Computer Systems Department Universidad Politecnica de Madrid 28031 Spain

A key countermeasure in cybersecurity has been the development of standardized computational protocols for modeling and sharing cyber threat intelligence (CTI) between organizations, enabling a shared understanding of threats and coordinated global responses. However, while the cybersecurity domain benefits from mature threat exchange frameworks, there has been little progress in the automatic and interoperable sharing of knowledge about disinformation campaigns. This paper proposes an open-source disinformation threat intelligence framework for sharing interoperable disinformation incidents. This approach relies on i) the modeling of disinformation incidents with the DISARM framework (MITRE ATT&CK-based TTP modeling of disinformation attacks), ii) a custom mapping to STIX2 standard representation (computational data format), and iii) an exchange architecture (called DISINFOX) capable of using the proposed mapping with a centralized platform to store and manage disinformation incidents and CTI clients which consume the gathered incidents. The microservice-based implementation validates the framework with more than 100 real-world disinformation incidents modeled, stored, shared, and consumed successfully. To the best of our knowledge, this work is the first academic and technical effort to integrate disinformation threats in the CTI ecosystem. © 2025, CC BY.

关键词： Cyber attacks

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Deep Learning-Assisted Parallel Interference Cancellation for Grant-Free NOMA in Machine-Type Communication

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IEEE Internet of Things Journal 2025年

作者： Oh, Yongjeong Jo, Jaehong Shim, Byonghyo Jeon, Yo-Seb POSTECH Department of Electrical Engineering Gyeongbuk Pohang37673 Korea Republic of Seoul National University Institute of New Media and Communications and the Department of Electrical and Computer Engineering Seoul08826 Korea Republic of

In this paper, we present a novel approach for joint activity detection (AD), channel estimation (CE), and data detection (DD) in uplink grant-free non-orthogonal multiple access (NOMA) systems. Our approach employs an iterative and parallel interference removal strategy inspired by parallel interference cancellation (PIC), enhanced with deep learning to jointly tackle the AD, CE, and DD problems. Based on this approach, we develop three PIC frameworks, each of which is designed for either coherent or non-coherence schemes. The first framework performs joint AD and CE using received pilot signals in the coherent scheme. Building upon this framework, the second framework utilizes both the received pilot and data signals for CE, further enhancing the performances of AD, CE, and DD in the coherent scheme. The third framework is designed to accommodate the non-coherent scheme involving a small number of data bits, which simultaneously performs AD and DD. Through joint loss functions and interference cancellation modules, our approach supports end-to-end training, contributing to enhanced performances of AD, CE, and DD for both coherent and non-coherent schemes. Simulation results demonstrate the superiority of our approach over traditional techniques, exhibiting enhanced performances of AD, CE, and DD while maintaining lower computational complexity. © 2014 IEEE.

关键词： Channel estimation

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Breaking the Barriers: An Active RIS-Enhanced DFRC System for Improved Multi-User Communication

Breaking the Barriers: An Active RIS-Enhanced DFRC System fo...

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2024 IEEE Global communications Conference, GLOBECOM 2024

作者： Patel, Ravi Singh, Keshav Mumtaz, Shahid Biswas, Sudip Indian Institute of Information Technology Department of Ece Guwahati781015 India National Sun Yat-sen University Institute of Communications Engineering Kaohsiung804 Taiwan Nottingham Trent University Department of Computer Science NG11 8NS United Kingdom

ISBN: (纸本)9798350351255

As we advance towards sixth-generation (6G) communications, the integration of dual-functional radar and communication (DFRC) systems with active reconfigurable intelligent surfaces (RIS) emerges as a promising solution to enhance spectrum efficiency. This work introduces an innovative DFRC system enhanced by an active RIS, capable of amplifying and phase-shifting signals to improve communication quality. We propose an optimization algorithm that maximizes combined data rates while considering constraints on radar probing power and power budgets for both DFRC and active RIS. Employing techniques such as weighted minimum mean square error (WMMSE) and fractional programming, our simulation results demonstrate that active RIS-enhanced DFRC systems significantly outperform passive RIS and non-RIS setups in terms of Weighted Sum Rate (WSR). Further analyses reveal that active RIS effectively mitigates multiplicative fading and enhances signal directivity, with performance gains influenced by the number of RIS elements, total system power, and radar detection power ratio. This work highlights the transformative potential of active RIS in optimizing next-generation wireless networks. © 2024 IEEE.

关键词： Budget control

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A Simple and Practical Underlay Scheme for Short-Range Secondary Communication

A Simple and Practical Underlay Scheme for Short-Range Secon...

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作者： Ibrahim, Mohamed Salah Karakasis, Paris A. Sidiropoulos, Nicholas D. University of Virginia Department of Electrical and Computer Engineering CharlottesvilleVA22904 United States InterDigital Communications ConshohockenPA19428 United States

The unprecedented growth in wireless Internet-of-Things and WiFi devices has renewed interest in mechanisms for efficient spectrum reuse. Existing schemes require some level of primary-secondary coordination, cross-channel state estimation and tracking, or activity detection-which complicate implementation. For low-power short-range secondary communication, the main impediment is strong and time-varying (e.g., intermittent) interference from the primary system. This paper proposes a practical underlay scheme that permits reliable secondary communication in this regime. The secondary transmitter merely has to send its signal twice, at very low power-a few dBs above the noise floor, but far below the primary's interference. Exploiting the repetition structure, reliable and computationally efficient recovery of the secondary signal is possible via canonical correlation analysis (CCA). Experiments using a software radio testbed reveal that, for a secondary user with only two receive antennas, reliable detection of the secondary signal is possible for signal to interference plus noise ratio (SINR) in the range of-20 to-40 dB. The approach works with unknown time-varying channels, digital or analog modulation, it is immune to carrier frequency offset, and, as a side-benefit, it provides means for accurate synchronization of the secondary user even at very low SINR. © 2002-2012 IEEE.

关键词： Signal to noise ratio

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Deep Learning and Latent Variables in Nonuniform Antenna Array Processing for Direction of Arrival 35

Deep Learning and Latent Variables in Nonuniform Antenna Arr...

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35th General Assembly and Scientific Symposium of the International Union of Radio Science, URSI GASS 2023

作者： Gomez-Talal, Ismael Bote-Curiel, Luis Rojo-Alvarez, Jose Luis Christodoulou, Christos Martinez-Ramon, Manel Universidad Rey Juan Carlos Department of Signal Theory and Communications and Telematic Systems and Computation Madrid Spain D!lemmaLab Ltd Startup Madrid Spain New Mexico University Department of Electrical and Computer Engineering United States

ISBN: (纸本)9789463968096

The problem of Direction of Arrival (DOA) in Antenna Array processing has been widely studied. Nonuniform spacing between consecutive elements of linear arrays gives particular advantages but is also challenging. Precedent solutions aimed to deal with it using standard and complex Deep Learning architectures. Given the simplicity of the complex DOA basic equations, we hypothesized that the intrinsic structure of DOA problems should correspond to well-defined manifolds in low-dimensional latent spaces and that this should also hold in nonuniform spatially distributed arrays. We benchmarked a variety of manifold learning estimators for DOA problems, namely, Principal Component Analysis, t-Distributed Stochastic Neighbor Embedding (tSNE), shallow and deep autoencoders (AE), and Uniform Manifold Active Projection (UMAP). The generated latent spaces exhibited intrinsic geometrical structures in one-dimensional manifolds with four branches. On the other hand, DOA recovery built upon fine-tuning these latent spaces exhibited better performance for nonuniform arrays using shallow AE architectures. Our results pave the way for using low-dimensional latent variable spaces in various electromagnetic problems based on the simplicity of the physical equations describing these technologies. © 2023 International Union of Radio Science.

关键词： Direction of arrival

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NeuroEvolution-based Hyperparameter Tuning for Reinforcement Learning in SDN Computation Offloading 7

NeuroEvolution-based Hyperparameter Tuning for Reinforcement...

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7th IET Smart Cities Symposium, SCS 2023

作者： Banerjee, Abhijit Gupta, Subir Dutta, P.K. El-Kenawy, El-Sayed M. Department of Electronics and Communication Engineering Dr. B C Roy Engineering College Durgapur India Department of Computer Science and Engineering Swami Vivekananda University Kolkata West Bengal 700121 School of Engineering and Technology Amity University Kolkata West Bengal India Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Mansoura Egypt

ISBN: (纸本)9781839539831

In this study, the application of NeuroEvolution-based hyperparameter tuning for reinforcement learning algorithms in the context of Software-Defined Networking (SDN) computation offloading was explored. The primary reinforcement learning algorithms investigated were Proximal Policy Optimization (PPO) and Asynchronous Advantage Actor-Critic (A3C). These algorithms were optimized using the Gamma Levy Hybrid Metaheuristic with Conditional Evolution (GLHM-CE) and Covariance Matrix Adaptation Evolution Strategy (CMA- ES) tuning methods. The performance of the algorithms was evaluated in terms of energy efficiency and reward comparison acrossepisodes, with a focus on SDN computation offloading scenarios. The results demonstrated that NeuroEvolution-based tuning, particularly when utilizing GLHM-CE optimization, significantly improved the energy efficiency of both PPO and A3C *** was concluded that the integration of NeuroEvolution-based hyperparameter tuning methods, such as GLHM-CE, with reinforcement learning algorithms, offers a promising approach for enhancing the performance of SDN computation offloading tasks. © The Institution of engineering & Technology 2023.

关键词： Reinforcement learning

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