Internet Technology Letters最新文献_第3页

Joint Optimization of User Association and Power Allocation in Wireless Networks Using a Large Spatio-Temporal Graph Transformer Model 基于大时空图变压器模型的无线网络用户关联与功率分配联合优化

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Internet Technology Letters Pub Date : 2025-09-19 DOI: 10.1002/itl2.70131

D. S. Keerthi, P. Vishwanath, Kothuri Parashu Ramulu, Gopinath Anjinappa, Hirald Dwaraka Praveena

{"title":"Joint Optimization of User Association and Power Allocation in Wireless Networks Using a Large Spatio-Temporal Graph Transformer Model","authors":"D. S. Keerthi, P. Vishwanath, Kothuri Parashu Ramulu, Gopinath Anjinappa, Hirald Dwaraka Praveena","doi":"10.1002/itl2.70131","DOIUrl":"https://doi.org/10.1002/itl2.70131","url":null,"abstract":"<div>\u0000 \u0000 <p>In this era, Wireless Communication Networks (WCNs) need dynamic and adaptive resource allocation approaches to handle user association and power allocation specifically under multi-connectivity and diverse traffic conditions. However, the conventional approaches struggle due to high computational cost, poor adaptability, and limited generalization. Therefore, this research proposes a large Spatio-Temporal Graph Transformer-based Reinforcement Learning (STGT-RL) model to jointly optimize user association and power allocation in large-scale WCNs. Initially, the network topology is designed using graph representations and incorporates a hybrid encoder that integrates Graph Transformers for spatial user-Base Station (BS) relationships and Spatio-Temporal Transformers for capturing time-varying traffic and channel states. Further, to ensure adaptive decision-making, a Transformer-RL policy agent is trained through a multi-objective reward function that assists in balancing throughput maximization and power efficiency. Furthermore, to enable stable policy learning, the model is initially trained using high-quality supervision from CRFSMA-generated labels, followed by reinforcement-based policy refinement. Hence, the experimental results are simulated on WCN environments to demonstrate that the proposed STGT-RL significantly outperforms baseline deep learning and heuristic-based methods in terms of throughput, energy efficiency, and fairness.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 6","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145101828","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Multi-Dimensional Feature Fusion Framework With XGBoost for IIoT-Driven Behavioral Analytics in Industrial Internet Systems 基于XGBoost的多维特征融合框架用于工业互联网系统中iiot驱动的行为分析

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Internet Technology Letters Pub Date : 2025-09-19 DOI: 10.1002/itl2.70144

Jiaqi Wang, Yunfeng Zhang, Yizhou He, Xiaolong Jiang

引用次数: 0

Design of an Intelligent Ground Wire Identification Device Based on IoT and RFID Technologies 基于物联网和RFID技术的智能地线识别装置设计

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Internet Technology Letters Pub Date : 2025-09-17 DOI: 10.1002/itl2.70097

Zhan Cui, Hongtao Zai, Yanfei Zhang, Jinguo Li, Peijun Wang, Ming Yuan

引用次数: 0

Enhancing Quality of Experience in Wireless English Education Platforms via Predictive Large Models 基于预测性大模型的无线英语教育平台体验质量提升

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Internet Technology Letters Pub Date : 2025-09-16 DOI: 10.1002/itl2.70137

Fei Li

引用次数: 0

Implementation of an IoT-Based Livestock Monitoring System Using Mioty Technology 基于物联网的家畜监测系统的实现

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Internet Technology Letters Pub Date : 2025-09-15 DOI: 10.1002/itl2.70141

Luis Rubio Fuentes, Andoni Beriain Rodríguez, Yuemin Ding

引用次数: 0

A Quantum-Inspired Bat and Harris Hawks Optimization Algorithm for Heterogeneous Wireless Sensor Networks 异构无线传感器网络的量子蝙蝠和哈里斯鹰优化算法

IF 0.5

Internet Technology Letters Pub Date : 2025-09-15 DOI: 10.1002/itl2.70138

Zuhair N. Mahmood, Salah A. Aliesawi

{"title":"A Quantum-Inspired Bat and Harris Hawks Optimization Algorithm for Heterogeneous Wireless Sensor Networks","authors":"Zuhair N. Mahmood, Salah A. Aliesawi","doi":"10.1002/itl2.70138","DOIUrl":"https://doi.org/10.1002/itl2.70138","url":null,"abstract":"<div>\u0000 \u0000 <p>Data aggregation is one major problem in heterogeneous wireless sensor networks (WSNs) where nodes possess varying sensing, computation, and communication capabilities. In order to fulfill the requirements of energy efficiency, latency, and optimization of the network lifetime, we introduce the QIBOA_HHO_Hybrid protocol, which is a mix of the Quantum-Inspired Binary Optimization Algorithm (QIBOA) and the Harris Hawks Optimization (HHO) algorithm. The hybrid protocol synergistically blends QIBOA's quantum-inspired parallel search to gain faster convergence with HHO's adaptive exploitation methods to optimize routing and clustering decisions dynamically. By prioritizing the most important energy-aware cluster head (CH) selection based on proximity and residual energy, the protocol balances the load and minimizes energy consumption. Simulation results verify that QIBOA_HHO_Hybrid outperforms conventional protocols SEP, DEEC, Z-SEP, and PSO-ECSM, with less latency, more throughput, and more network lifetime. By fusing quantum optimization while simulations suggest a compromise with energy efficiency and latency compared to some existing protocols, adaptive clustering, and HHO's cooperative predation-inspired methods, scalability and reliability are enhanced in dynamic environments, and it is a trusted solution to large-scale heterogeneous WSNs.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 6","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145057823","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimized Dual-Attention Convolutional Neural Networks for Hybrid Beamforming and High-Precision Channel Estimation in 5G Massive MIMO Wireless Communications Systems 5G海量MIMO无线通信系统中混合波束形成和高精度信道估计的优化双注意力卷积神经网络

IF 0.5

Internet Technology Letters Pub Date : 2025-09-15 DOI: 10.1002/itl2.70129

Sandeep Prabhu, Humaira Nishat, Shreenidhi Krishnamurthy Subramaniyan, Harishchander Anandaram, Shargunam Selvam

{"title":"Optimized Dual-Attention Convolutional Neural Networks for Hybrid Beamforming and High-Precision Channel Estimation in 5G Massive MIMO Wireless Communications Systems","authors":"Sandeep Prabhu, Humaira Nishat, Shreenidhi Krishnamurthy Subramaniyan, Harishchander Anandaram, Shargunam Selvam","doi":"10.1002/itl2.70129","DOIUrl":"https://doi.org/10.1002/itl2.70129","url":null,"abstract":"<div>\u0000 \u0000 <p>Beamforming and channel estimation are fundamental components of 5G massive MIMO (multiple-input–multiple-output) systems, particularly in the millimeter-wave (mmWave) spectrum, where high-frequency transmissions are susceptible to path loss and signal degradation. The growing demand for ultrareliable low-latency communication (URLLC) and high-quality services necessitates advanced, adaptive techniques to manage the highly dynamic nature of mmWave channels. This study proposes a novel framework that integrates dual-attention convolutional neural networks (DSCN-PAN) with reformed poplar optimization (RePO) to enhance beamforming accuracy and channel estimation efficiency in 5G massive MIMO systems. Compared to conventional methods, the proposed model demonstrates significant performance gains, including over 90% improvement in spectral efficiency, 99.41% beam alignment precision, a 99.5% enhancement in Channel State Information (CSI) estimation, and a 99.2% reduction in bit error rate (BER). The DSCN-PAN-RePO architecture effectively supports dynamic and complex communication environments, offering a scalable and energy-efficient solution for next-generation wireless networks.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 6","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058089","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimization on Multiple-Input and Multiple-Output (MIMO) Network Affect Performance of an Radio Frequency (RF) in 6G 多输入多输出（MIMO）网络优化对6G射频（RF）性能的影响

IF 0.5

Internet Technology Letters Pub Date : 2025-09-15 DOI: 10.1002/itl2.70139

Bilal A. Ozturk, Ibrahim Ahmad Yousef Alkhatib, Olivia Zuhair Hejaz, Anas Atef Shamaileh, Mutasem Azmi Al-Karablieh, Musab Alqudah, Manal Hasan Jamil Barqawi, Lena Farrah, Sujood Shahin alkhrisat

{"title":"Optimization on Multiple-Input and Multiple-Output (MIMO) Network Affect Performance of an Radio Frequency (RF) in 6G","authors":"Bilal A. Ozturk, Ibrahim Ahmad Yousef Alkhatib, Olivia Zuhair Hejaz, Anas Atef Shamaileh, Mutasem Azmi Al-Karablieh, Musab Alqudah, Manal Hasan Jamil Barqawi, Lena Farrah, Sujood Shahin alkhrisat","doi":"10.1002/itl2.70139","DOIUrl":"https://doi.org/10.1002/itl2.70139","url":null,"abstract":"<div>\u0000 \u0000 <p>In this article, we introduce the reconfigurable intelligent surfaces (RISs) restrict their general adoption, which employs digital pre-distortion, deep learning-based correction, and adaptive filtering to counteract real-time RF impairments. The technique is highly applicable to future 6G networks because it enhances MIMO performance by reducing BER, improving phase noise resilience, and achieving the highest spectral efficiency. Thermal noise, phase noise, and nonlinearity loss are RF impairments that significantly reduce the effectiveness of MIMO communication in 6G networks. Signal distortion, phase instability, and spectrum inefficiencies are the consequences of these impairments, which further increase BER and reduce capacity. A dynamic distortion mitigation framework is required because conventional compensating strategies cannot respond to new scenarios in real time. These approaches come with extra latency and power usage, making them less suitable for real-time use in 6G. However, there remains a challenge to using ML-based adaptive filtering on high-speed and low-power hardware, even though it has been at the forefront regarding dynamically compensating RF impairments. The cost and complexity of deployment of hybrid beamforming and reconfigurable intelligent surfaces (RISs) restrict their general adoption, yet they enhance MIMO performance in RF impairment. The basic challenge for smooth operation in 6G-enabled MIMO systems is to develop adaptive, low-power, and computationally efficient solutions.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 6","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145058088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Real-Time Intelligent Detection of APT Attacks Using Mobile Edge Networks 基于移动边缘网络的APT攻击实时智能检测

IF 0.5

Internet Technology Letters Pub Date : 2025-09-12 DOI: 10.1002/itl2.70132

Xiwei Wang

引用次数: 0

Lightweight Vision-Language Model for Fashion Design in IoT Environment 物联网环境下服装设计的轻量级视觉语言模型

IF 0.5

Internet Technology Letters Pub Date : 2025-09-12 DOI: 10.1002/itl2.70140

Na Wang

{"title":"Lightweight Vision-Language Model for Fashion Design in IoT Environment","authors":"Na Wang","doi":"10.1002/itl2.70140","DOIUrl":"https://doi.org/10.1002/itl2.70140","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid development of the Internet of Things (IoT), the demand for personalized fashion design in the IoT environment is growing, and fashion recommendation has gradually become a new research hotspot. However, existing fashion recommendation methods are often designed based on a single modality and contain a large number of parameters, making them unable to be effectively deployed on IoT edge devices with limited computing ability. Inspired by this, this paper proposes a novel personalized fashion color recommendation (FashionCR) framework based on a lightweight large vision-language model for fashion design in the IoT environment. Specifically, this framework consists of an IoT-based fashion color recommendation system and the FashionCR model. The recommendation system mainly introduces how to train the FashionCR model and deploy it to the edge devices. The FashionCR model leverages the visual branch of the CLIP model to accurately learn the physiological features of different individuals, such as skin color and face shape, and utilizes the text branch to efficiently process the text intentions input by users. Meanwhile, in order to meet the limited resources of the IoT environment, a lightweight modification has been implemented to the CLIP model. In addition, the 4-season color theory is integrated into the FashionCR framework to achieve accurate color recommendation. Experimental results show that this framework performs excellently in various metrics, providing a new solution for the field of fashion design in the IoT environment and effectively improving the accuracy and personalization of color recommendation.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 6","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145038180","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0