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Enhancing Wireless Networks with Attention Mechanisms: Insights from Mobile Crowdsensing

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arXiv 2024年

作者： Yang, Yaoqi Du, Hongyang Xiong, Zehui Niyato, Dusit Jamalipour, Abbas Han, Zhu College of Communications Engineering Army Engineering University of PLA Nanjing210000 China College of Computing and Data Science NTU Singapore Singapore Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore Singapore School of Electrical and Computer Engineering University of Sydney SydneyNSW2006 Australia Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States

The increasing demand for sensing, collecting, transmitting, and processing vast amounts of data poses significant challenges for resource-constrained mobile users, thereby impacting the performance of wireless networks. In this regard, from a case of mobile crowdsensing (MCS), we aim at leveraging attention mechanisms in machine learning approaches to provide solutions for building an effective, timely, and secure MCS. Specifically, we first evaluate potential combinations of attention mechanisms and MCS by introducing their preliminaries. Then, we present several emerging scenarios about how to integrate attention into MCS, including task allocation, incentive design, terminal recruitment, privacy preservation, data collection, and data transmission. Subsequently, we propose an attention-based framework to solve network optimization problems with multiple performance indicators in large-scale MCS. The designed case study have evaluated the effectiveness of the proposed framework. Finally, we outline important research directions for advancing attention-enabled MCS. © 2024, CC BY.

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Lightweight Wireless Sensing Through RIS and Inverse Semantic Communications

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Lightweight Wireless Sensing Through RIS and Inverse Semanti...

IEEE Conference on Wireless Communications and Networking

作者： Hongyang Du Jiacheng Wang Dusit Niyato Jiawen Kang Zehui Xiong Junshan Zhang Xuemin Sherman Shen The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering University of California Davis USA The Department of Electrical and Computer Engineering University of Waterloo Canada

Thanks to the ubiquitous and easily accessible nature of wireless signals, wireless sensing is regarded as one of the promising techniques in the next-generation Internet of Things. In this paper, we propose the inverse semantic communications as a new paradigm to achieve lightweight wireless sensing using the reconfigurable intelligent surface (RIS). Instead of extracting semantic information from messages, we aim to encode the task-related source messages into a hyper-source message. Specifically, we first develop a novel RIS hardware for encoding several signal spectrums into one MetaSpectrum. We then propose a self-supervised learning method for decoding the MetaSpectrums to obtain the original signal spectrums. Using the sensing data collected from the real world, we show that our framework can reduce the data volume by 90% compared to that before encoding, without affecting the execution of various sensing tasks. Experiment results also demonstrate that the amplitude response matrix of the RIS enables the encryption of the sensing data.

关键词： Wireless communication Wireless sensor networks Semantics Self-supervised learning Encoding Sensors Decoding

Greeting Gesture Analysis Using Boosting Algorithms and SHAP

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Greeting Gesture Analysis Using Boosting Algorithms and SHAP

International Symposium on Soft Computing and Intelligent systems (SCIS)

作者： Angga Wahyu Wibowo Eri Sato-Shimokawara Kurnianingsih Department of Computer Science Graduate School of Systems Design Tokyo Metropolitan University Tokyo Japan Department of Electrical Engineering Politeknik Negeri Semarang Semarang Indonesia

ISBN: (数字)9798350373332

ISBN: (纸本)9798350373349

Recently, studies related to human activity recognition have developed which have been applied in various fields. In that field Machine learning and deep learning techniques have been widely used for several classification and prediction tasks. However, the first problem is that there is rarely any research on human activities that reflect the culture of a region, such as greeting gestures. Second, there are few studies that do not provide models resulting from the classification or prediction process using machine learning, which can result in a lack of understanding of how a model from machine learning is generated. This study aims to predict Japanese greeting gestures (eshaku, keirei, saikeirei, waving hand) and Indonesian (placing both hands in front of the chest) using Light Gradient Boosting Machine (LightGBM), eXtreme Gradient Boosting (XGBoost), and Gradient Boosting. Then, represent the model of the learning machine using SHapley Additive exPlanations (SHAP) to find out how the learning machine obtain a model. Our findings show the efficacy of this method and show that the model not only predicts greeting gestures with high accuracy but also offers a transparent understanding of the factors influencing its predictions, thus enhancing the interpretability and applicability of machine learning in recognizing culturally significant human activities. In the future, we plan to use machine learning and other Explainable Artificial Intelligence (XAI) methods to study human activities with cultural concepts such as greeting gestures in different styles, create more greeting gesture-based human activity datasets, and examine the ethical implications or considerations of using machine learning in cultural contexts to respect cultural differences.

关键词： Deep learning Ethics Machine learning algorithms Additives Explainable AI Machine learning Predictive models Boosting Cultural differences Human activity recognition

computer-integrated system of automatic balance control in centrifuge rotors with variable imbalance 5

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Computer-integrated system of automatic balance control in c...

5th IEEE International Conference on Modern electrical and Energy System, MEES 2023

作者： Pavlenko, Volodymyr Kurliak, Petro Horiashchenko, Serhiy Volianyk, Oleksii Batsala, Yaroslav Nikitchuk, Tetiana Kyiv National University of Technologies and Design Department of Information and Computer Technologies Kyiv Ukraine Ivano-Frankivsk National Technical University of Oil and Gas Department of Electrical Power Engineering Ivano-Frankivsk Ukraine Electromechanical and Energy Systems Khmelnytskyi National University Department of Machines and Devices Khmelnytskyi Ukraine Kyiv National University of Technologies and Design Department of Mechanical Engineering Kyiv Ukraine Zhytomyr Polytechnic State University Department of Computer Technologies in Medicine and Telecommunications Zhytomyr Ukraine

ISBN: (纸本)9798350359787

The paper presents the developed computer-integrated system of automatic control of rotors balancing in centrifuges with variable imbalance. It includes a microcontroller, a Hall sensor, a computer-oriented Bond Graph model of an asynchronous motor, and a control program that, according to the proposed algorithm, checks the nominal and critical value of the centrifuge drive current. At the same time, the current values are recorded and the current is monitored. When the current increases, the system automatically resets the revolutions by 10% to reduce the amplitude of vibrations in the transient modes of their rotation with further control of the permissible current limit and engine load. © 2023 IEEE.

关键词： Centrifuges

Hierarchical Micro-Segmentations for Zero-Trust Services via Large Language Model (LLM)-enhanced Graph Diffusion

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arXiv 2024年

作者： Liu, Yinqiu Liu, Guangyuan Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui In Kim, Dong Shen, Xuemin College of Computing and Data Science Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Department of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of Department of Electrical and Computer Engineering University of Waterloo Canada

—In the rapidly evolving Next-Generation Networking (NGN) era, the adoption of zero-trust architectures has become increasingly crucial to protect security. However, provisioning zero-trust services in NGNs poses significant challenges, primarily due to the environmental complexity and dynamics. Motivated by these challenges, this paper explores efficient zero-trust service provisioning using hierarchical micro-segmentations. Specifically, we model zero-trust networks via hierarchical graphs, thereby jointly considering the resource- and trust-level features to optimize service efficiency. We organize such zero-trust networks through micro-segmentations, which support granular zero-trust policies efficiently. To generate the optimal micro-segmentation, we present the Large Language Model-Enhanced Graph Diffusion (LEGD) algorithm, which leverages the diffusion process to realize a high-quality generation paradigm. Additionally, we utilize policy boosting and Large Language Models (LLM) to enable LEGD to optimize the generation policy and understand complicated graphical features. Moreover, realizing the unique trustworthiness updates or service upgrades in zero-trust NGN, we further present LEGD-Adaptive Maintenance (LEGD-AM), providing an adaptive way to perform task-oriented fine-tuning on LEGD. Extensive experiments demonstrate that the proposed LEGD achieves 90% higher efficiency in provisioning services compared with other baselines. Moreover, the LEGD-AM can reduce the service outage time by over 50%. © 2024, CC BY.

关键词： Diffusion

User Grouping-Based Hierarchical Rate-Splitting Multiple Access for Reconfigurable Intelligent Surface-Assisted Downlink Communication

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Yang, Zhixiang Feng, Lei Zhou, Fanqin Xie, Kunyi Qiu, Xuesong Xiong, Zehui Yuen, Chau Han, Zhu Beijing University of Posts and Telecommunications State Key Laboratory of Networking and Switching Technology Beijing100876 China Singapore University of Technology and Design Pillar of Information Systems Technology and Design Singapore487372 Singapore Nanyang Technological University School of Electrical and Electronic Engineering Singapore639798 Singapore University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

The joint optimization of rate-splitting multiple access (RSMA) and reconfigurable intelligent surface (RIS) offers a mutually beneficial solution. In this paper, we study a RIS-assisted downlink user grouping-based hierarchical RSMA communication network, where the base station transmits the common streams and private streams simultaneously to serve multiple users. The sum rate (SR) optimization problem is constructed to jointly optimize user grouping, beamforming, and rate splitting. To tackle the NP-hard problem, a user grouping algorithm is first provided to form the hierarchical RSMA model. Next, an equivalent weighted minimum mean-square error (WMMSE) problem is constructed and a WMMSE-based block coordinate descent (BCD) algorithm is designed to update the remaining variables in an iterated way. Specifically, the optimization of transmit beamforming and the rate splitting matrix is reduced to solving a typical convex quadratically constrained quadratic program problem. The solution for passive beamforming is recovered from the intermediate result obtained by the manifold optimization method. Finally, the process of the BCD algorithm is presented. The numerical results indicate that the proposed scheme evidently surpasses one-layer RSMA scheme, NOMA scheme, SDMA scheme, and no RIS scheme, especially in overloaded scenarios. The proposed scheme further increases the SR of common steams compared to the hierarchical RSMA scheme and significantly reduces computational complexity compared to the generalized RSMA scheme. © 2015 IEEE.

关键词： Mean square error

Myopically Verifiable Probabilistic Certificates for Safe Control and Learning

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arXiv 2024年

作者： Wang, Zhuoyuan Jing, Haoming Kurniawan, Christian Chern, Albert Nakahira, Yorie The Department of Electrical and Computer Engineering Carnegie Mellon Universty PA15213 United States The Information Systems Technology and Design Pillar Singapore University of Technology and Design Singapore487372 Singapore The Department of Computer Science and Engineering University of California San DiegoCA92093 United States

This paper addresses the design of safety certificates for stochastic systems, with a focus on ensuring long-term safety through fast real-time control. In stochastic environments, set invariance-based methods that restrict the probability of risk events in infinitesimal time intervals may exhibit significant long-term risks due to cumulative uncertainties/risks. On the other hand, reachability-based approaches that account for the long-term future may require prohibitive computation in real-time decision making. To overcome this challenge involving stringent long-term safety vs. computation tradeoffs, we first introduce a novel technique termed 'probabilistic invariance'. This technique characterizes the invariance conditions of the probability of interest. When the target probability is defined using long-term trajectories, this technique can be used to design myopic conditions/controllers with assured long-term safe probability. Then, we integrate this technique into safe control and learning. The proposed control methods efficiently assure long-term safety using neural networks or model predictive controllers with short outlook horizons. The proposed learning methods can be used to guarantee long-term safety during and after training. Finally, we demonstrate the performance of the proposed techniques in numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Stochastic systems

Guiding AI-Generated Digital Content with Wireless Perception

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arXiv 2023年

作者： Wang, Jiacheng Du, Hongyang Niyato, Dusit Xiong, Zehui Kang, Jiawen Mao, Shiwen Shen, Xuemin The School of Computer Science and Engineering Nanyang Technological University Singapore The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The School of Automation Guangdong University of Technology China The Department of Electrical and Computer Engineering Auburn University Auburn United States The Department of Electrical and Computer Engineering University of Waterloo Canada

Recent advances in artificial intelligence (AI), coupled with a surge in training data, have led to the widespread use of AI for digital content generation, with ChatGPT serving as an representative example. Despite the increased efficiency and diversity, the inherent instability of AI models poses a persistent challenge in guiding these models to produce the desired content for users. In this paper, we introduce an integration of wireless perception (WP) with AI-generated content (AIGC) and propose a unified WP-AIGC framework to improve the quality of digital content production. The framework employs a novel multi-scale perception technology to read user’s posture, which is difficult to describe accurately in words, and transmits it to the AIGC model as skeleton images. Based on these images and user’s service requirements, the AIGC model generates corresponding digital content. Since the production process imposes the user’s posture as a constraint on the AIGC model, it makes the generated content more aligned with the user’s requirements. Additionally, WP-AIGC can also accept user’s feedback, allowing adjustment of computing resources at edge server to improve service quality. Experiments results verify the effectiveness of the WP-AIGC framework, highlighting its potential as a novel approach for guiding AI models in the accurate generation of digital content. © 2023, CC BY.

关键词： Quality of service

A Unified Framework for Guiding Generative AI with Wireless Perception in Resource Constrained Mobile Edge Networks

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arXiv 2023年

作者： Wang, Jiacheng Du, Hongyang Niyato, Dusit Kang, Jiawen Xiong, Zehui Rajan, Deepu Mao, Shiwen Shen, Xuemin The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Automation Guangdong University of Technology China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore The Department of Electrical and Computer Engineering Auburn University Auburn United States The Department of Electrical and Computer Engineering University of Waterloo Canada

With the significant advancements in artificial intelligence (AI) technologies and powerful computational capabilities, generative AI (GAI) has become a pivotal digital content generation technique for offering superior digital services. However, directing GAI towards desired outputs still suffer the inherent instability of the AI model. In this paper, we design a novel framework that utilizes wireless perception to guide GAI (WiPe-GAI) for providing digital content generation service, i.e., AI-generated content (AIGC), in resource-constrained mobile edge networks. Specifically, we first propose a new sequential multi-scale perception (SMSP) algorithm to predict user skeleton based on the channel state information (CSI) extracted from wireless signals. This prediction then guides GAI to provide users with AIGC, such as virtual character generation. To ensure the efficient operation of the proposed framework in resource constrained networks, we further design a pricing-based incentive mechanism and introduce a diffusion model based approach to generate an optimal pricing strategy for the service provisioning. The strategy maximizes the user’s utility while enhancing the participation of the virtual service provider (VSP) in AIGC provision. The experimental results demonstrate the effectiveness of the designed framework in terms of skeleton prediction and optimal pricing strategy generation comparing with other existing solutions. © 2023, CC BY.

关键词： Quality of service