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Optimization of the Downlink Spectral- and Energy- Efficiency of RIS-Aided Multi-User URLLC MIMO systems

IEEE Transactions on Communications 2025年第5期73卷 3497-3513页

作者： Soleymani, Mohammad Santamaria, Ignacio Jorswieck, Eduard A. Schober, Robert Hanzo, Lajos Universität Paderborn Signal and System Theory Group Paderborn33098 Germany Universidad de Cantabria Department of Communications Engineering Santander39005 Spain Technische Universität Braunschweig Institute for Communications Technology Braunschweig38106 Germany Institute for Digital Communications Erlangen91058 Germany University of Southampton Department of Electronics and Computer Science SouthamptonSO17 1BJ United Kingdom

Modern wireless communication systems are expected to provide improved latency and reliability. To meet these expectations, a short packet length is needed, which makes the first-order Shannon rate an inaccurate performance metric for such communication systems. A more accurate approximation of the achievable rates of finite-block-length (FBL) coding regimes is known as the normal approximation (NA). It is therefore of substantial interest to study the optimization of the FBL rate in multi-user multiple-input multiple-output (MIMO) systems, in which each user may transmit and/or receive multiple data streams. Hence, we formulate a general optimization problem for improving the spectral and energy efficiency of multi-user MIMO-aided ultra-reliable low-latency communication (URLLC) systems, which are assisted by reconfigurable intelligent surfaces (RISs). We show that an RIS is capable of substantially improving the performance of multi-user MIMO-aided URLLC systems. Moreover, the benefits of RIS increase as the packet length and/or the tolerable bit error rate are reduced. This reveals that RISs can be even more beneficial in URLLC systems for improving the FBL rates than in conventional systems approaching Shannon rates. © 1972-2012 IEEE.

关键词： Spectrum efficiency

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A third-party platoon coordination service: Pricing under government subsidies

A third-party platoon coordination service: Pricing under go...

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作者： Bai, Ting Johansson, Alexander Li, Shaoyuan Johansson, Karl Henrik Mårtensson, Jonas School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden KTH Royal Institute of Technology Stockholm Sweden Department of Automation Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University Shanghai China Digital Futures Stockholm Sweden

This paper models a platooning system consisting of trucks and a third-party service provider (TPSP), which performs platoon coordination, distributes the platooning profit in platoons, and charges trucks in exchange for the services. Government subsidies used to incentivize platooning are also considered. We propose a pricing rule for the TPSP, which keeps part of the platooning profit including the subsidy each time a platoon is formed. In addition, a platoon coordination solution based on the distributed model predictive control (MPC) is proposed, in which the pricing rule under government subsidies is integrated. We perform a realistic simulation over the Swedish road network to evaluate the impact of the pricing rule and subsidies on the achieved profits and fuel savings. Our results show that subsidies are an effective mean to boost fuel savings from platooning. Moreover, the simulation study indicates that high pricing corresponds to a low platooning rate of the system, as trucks' incentives for platooning decrease. © 2023 The Authors. Asian Journal of Control published by John Wiley & Sons Australia, Ltd on behalf of Chinese Automatic Control Society.

关键词： Trucks

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A new quantum-inspired pattern based on Goldner-Harary graph for automated alzheimer’s disease detection

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Cognitive Neurodynamics 2025年第1期19卷 1-19页

作者： Sercek, Ilknur Sampathila, Niranjana Tasci, Irem Ekmekyapar, Tuba Tasci, Burak Barua, Prabal Datta Baygin, Mehmet Dogan, Sengul Tuncer, Turker Tan, Ru-San Acharya, U.R. Department of Digital Forensics Engineering College of Technology Firat University Elazig Turkey Department of Biomedical Engineering Manipal Academy of Higher Education Manipal India Department of Neurology School of Medicine Firat University Elazig 23119 Turkey Department of Neurology Malatya Training and Research Hospital Malatya 44000 Turkey Vocational School of Technical Sciences Firat University Elazig 23119 Turkey School of Business (Information System) University of Southern Queensland Toowoomba Australia Department of Computer Engineering College of Engineering Erzurum Technical University Erzurum Turkey Department of Cardiology National Heart Centre Singapore Singapore Singapore Duke-NUS Medical School Singapore Singapore School of Mathematics Physics and Computing University of Southern Queensland Springfield Australia

Alzheimer's disease (AD) is a common cause of dementia. We aimed to develop a computationally efficient yet accurate feature engineering model for AD detection based on electroencephalography (EEG) signal inputs. New method: We retrospectively analyzed the EEG records of 134 AD and 113 non-AD patients. To generate multilevel features, a multilevel discrete wavelet transform was used to decompose the input EEG-signals. We devised a novel quantum-inspired EEG-signal feature extraction function based on 7-distinct different subgraphs of the Goldner-Harary pattern (GHPat), and selectively assigned a specific subgraph, using a forward-forward distance-based fitness function, to each input EEG signal block for textural feature extraction. We extracted statistical features using standard statistical moments, which we then merged with the extracted textural features. Other model components were iterative neighborhood component analysis feature selection, standard shallow k-nearest neighbors, as well as iterative majority voting and greedy algorithm to generate additional voted prediction vectors and select the best overall model results. With leave-one-subject-out cross-validation (LOSO CV), our model attained 88.17% accuracy. Accuracy results stratified by channel lead placement and brain regions suggested P4 and the parietal region to be the most impactful. Comparison with existing methods: The proposed model outperforms existing methods by achieving higher accuracy with a computationally efficient quantum-inspired approach, ensuring robustness and generalizability. Cortex maps were generated that allowed visual correlation of channel-wise results with various brain regions, enhancing model explainability. © The Author(s) 2025.

关键词： Alzheimer’s disease Brain-computer interface EEG GHPat Goldner-Harary graph Signal classification

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Brain Tumor Classification system Using Decision Tree Algorithm

Brain Tumor Classification System Using Decision Tree Algori...

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Cybernetics and Innovations (ICCI), International Conference on

作者： Sattarpoom Thaiparnit Thanakrit Janchidfah Adil Farooq Dep. Of Information System and Computer Business Faculty of Business Administration Rajamangala University of Technology Suvarnabhumi Suphan Buri Thailand dep. Of Digital Media Technology Muban Chombueng Rajabhat University Ratchaburi Thailand Department of Electronic Engineering Maynooth University Ireland

ISBN: (数字)9798331533267

ISBN: (纸本)9798331533274

This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is to assist medical personnel in making decisions, as distinguishing between two types of brain tumors-benign and malignant (cancerous)-can be challenging, especially for less experienced medical staff. Due to the similarities between these two types of tumors, it may be difficult for medical practitioners with limited expertise to differentiate between them in a timely manner. The proposed brain tumor classification system is designed to address this challenge. The research team conducted the study over approximately seven months, starting from the second semester of the 2023 academic year through the first semester of the 2024 academic year. Experimental results revealed that among the tree-based algorithms, Random Forest achieved the highest accuracy, followed by M5P. The best average accuracy from the experiments was obtained using a 70% training and 30% testing split, yielding an accuracy of 96.83%. Therefore, the research team selected the 70% training and 30% testing split for model development, as it provided the highest accuracy compared to the 60% training and 40% testing split, and the 80% training and 20% testing split, which showed lower accuracy. The results demonstrate that the 70% training and 30% testing approach is optimal for the brain tumor classification system, ensuring high accuracy in classifying brain tumors.

关键词： Training Technological innovation Accuracy Machine learning algorithms Brain tumors Brain modeling Classification algorithms Decision trees Testing Cancer

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Identifying superword level parallelism with extended directed dependence graph reachability

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Science China(Information Sciences) 2017年第1期60卷 214-216页

作者： Jie ZHAO Rongcai ZHAO National Digital Switching System Engineering & Technological Research Center Computer Science Department cole Normale Supérieure

Dear editor,The increasing trend of multimedia applications’proliferation brings about multimedia extensions’wide use among existing microprocessors of mainstream manufacturers,e.g.,Intel’s MMX,AMD’s3DNow!,IBM’s VMX/Altivec,***,the implementation details behind these multimedia extensions vary from one architecture to another;hence,it generally comes in form of SIMD(single

关键词： node SIMD Identifying superword level parallelism with extended directed dependence graph reachability SLP

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A virtual service placement approach based on improved quantum genetic algorithm

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Frontiers of Information Technology & Electronic engineering 2016年第7期17卷 661-671页

作者： Gang XIONG Yu-xiang HU Le TIAN Ju-long LAN Jun-fei LI Qiao ZHOU National Digital Switching System Engineering&Technological Research Center Zhengzhou 450002China Department of Mathematics and Computer Science University of AntwerpAntwerp 2020Belgium

Despite the critical role that middleboxes play in introducing new network functionality,management and innovation of them are still severe challenges for network operators,since traditional middleboxes based on hardware lack service flexibility and ***,though new networking technologies,such as network function virtualization(NFV) and softwaredefined networking(SDN),are considered as very promising drivers to design cost-efficient middlebox service architectures,how to guarantee transmission efficiency has drawn little attention under the condition of adding virtual service process for ***,we focus on the service deployment problem to reduce the transport delay in the network with a combination of NFV and ***,a framework is designed for service placement decision,and an integer linear programming model is proposed to resolve the service placement and minimize the network transport *** a heuristic solution is designed based on the improved quantum genetic *** results show that our proposed method can calculate automatically the optimal placement *** scheme can achieve lower overall transport delay for a network compared with other schemes and reduce 30% of the average traffic transport delay compared with the random placement scheme.

关键词： Software-defined networking(SDN) Network function virtualization Quantum genetic algorithm Middlebox

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A proactive defense mechanism for mobile communication user data

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Science China(Information Sciences) 2018年第10期61卷 266-268页

作者： Caixia LIU Xinsheng JI Jiangxing WU Xiao QIN The National Digital Switching System Engineering & Technological R&D Center Department of Computer Science and Software Engineering Samuel Ginn College of EngineeringAuburn University

Dear editor,Several studies have recently reported on major vulnerabilities in the Signaling system No.7 (SS7)used in mobile networks [1, 2]. The reported vulnerabilities and security issues would lead to the illegal acquisition and tampering of mobile communication user data, known as cellphone user data. The cellphone user data contain important information such as identity identification, location identification, security parameter-set. Due to

关键词： A proactive defense mechanism for mobile communication user data MSISDN

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LDGCN: An Edge-End Lightweight Dual GCN Based on Single-Channel EEG for Driver Drowsiness Monitoring

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IEEE Transactions on Consumer Electronics 2025年

作者： Huang, Jingwei Wang, Chuansheng Huang, Jiayan Fan, Haoyi Xue, Xingsi Zhang, Fuquan Fuzhou University College of Computer and Big Data Fuzhou China Polytechnic University of Catalonia Department of Automatic Control Barcelona Spain Putian University New Engineering Industry College Putian China Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Fuzhou350118 China Minjiang University Fujian Provincial Key Laboratory of Information Processing and Intelligent Control Fuzhou China Minjiang University College of Computer and Control Engineering Fuzhou China Sichuan Conservatory of Music Digital Media Art Key Laboratory of Sichuan Province Chengdu China Minjiang University Fuzhou Technology Innovation Center of Intelligent Manufacturing information System Fuzhou China Fuzhou China

Driver drowsiness electroencephalogram (EEG) signal monitoring can promptly alert drivers of their drowsiness in edge-end Consumer Electronics (CE), thereby reducing the probability of traffic accidents. Graph convolutional networks (GCNs) have shown significant advancements in processing the non-stationary, time-varying, and non-Euclidean nature of EEG signals. However, the existing single-channel EEG adjacency graph construction process lacks interpretability, which hinders the ability of GCNs to effectively extract adjacency graph features, thus affecting the performance of drowsiness monitoring. To address this issue, we propose an edge-end Lightweight Dual Graph Convolutional Network (LDGCN). Specifically, we are the first to incorporate neurophysiological knowledge to design a Baseline Drowsiness Status Adjacency Graph (BDSAG), which characterizes driver drowsiness status. Additionally, to express more features within limited EEG data, we introduce the Augmented Graph-level Module (AGM). This module captures global and local information at the graph level, ensuring that BDSAG features remain intact while enhancing effective feature expression capability. To further enhance the application of CE, we apply Adaptive Pruning Optimization (APO) to the channels and neurons of LDGCN, which nearly halves the inference latency. Experiments on benchmark datasets demonstrate that LDGCN offers the best trade-off between monitoring performance and hardware resource utilization, outperforming existing state-of-the-art algorithms. © 1975-2011 IEEE.

关键词： Neurons

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Use multiplexing to increase information in QR code

Use multiplexing to increase information in QR code

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8th International Conference on computer Science and Education, ICCSE 2013

作者： Vongpradhip, Sartid Digital System Engineering Laboratory Department of Computer Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781467344623

In this paper a novel approach to multiplex data in QR Code is presented. This technique can increase the amount of data, as the original information, in QR Code as well as keeping secret information. The original data for encoding is divided into smaller parts, each part will form QR Code pattern in its standard form. Each pattern is encoded or multiplexed and represented each module in QR Code with black and white special symbols. At the receiving end, this QR Code with special symbols (that was multiplexed) is decoded to give back the number of QR Code patterns that was multiplexed. These QR Code pattern can be read by the general QR Code reader and the data can be concatenated back to form its original information. © 2013 IEEE.

关键词： Concatenated codes

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Cryptanalysis and Improvement of a Chaotic Map-Control-Based and the Plain Image-Related Cryptosystem

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computers, Materials & Continua 2019年第8期61卷 687-699页

作者： Bin Lu Fenlin Liu Xin Ge Zhenyu Li China National Digital Switching System Engineering Technology Research Center ZhengzhouChina Department of Computer Science University of YorkDeramor LaneHeslingtonUK

Due to the characteristics of chaotic systems,different cryptosystems based on chaos have been proposed to satisfy the security of multimedia data.A plain image-related chaotic algorithm is proposed by Luo et *** high speed and *** weaknesses of the cryptosystem are studied in this *** is found that the important secret key information is leaked because an important parameter can be obtained after an inverse operation in the last step of the cryptosystems without secret ***,the value zero is processed improperly in quantification *** on the weaknesses,chosen plaintext attack on the cryptosystem is proposed,by which,an important parameter,equivalent to secret key,can be calculated with a specific chosen plain *** the obtained parameter,the plain image of any ciphered image,encrypted by the cryptosystem,can be ***,an improvement is proposed to solve the problems after modifying the quantification *** is from the experiments that chosen plaintext attack is valid and improved algorithm possesses better performance.

关键词： Multimedia cryptosystem cryptanalysis chaos chosen plaintext attack

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