Internet Technology Letters最新文献

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

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

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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

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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

Resource Scheduling Model in Computing Power Network: An Efficient and Low-Carbon Approach Using Game Theory 计算能力网络资源调度模型：基于博弈论的高效低碳方法

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Internet Technology Letters Pub Date : 2025-09-12 DOI: 10.1002/itl2.70111

Yunhao Zhang, Zhiyu Jiang, Xiuping Guo, Xueying Zhai, Yunfeng Peng

引用次数: 0

Safety Fault Prediction and Diagnosis of Power Measurement Equipment Based on 6G Big Data Analysis 基于6G大数据分析的功率测量设备安全故障预测与诊断

IF 0.5

Internet Technology Letters Pub Date : 2025-09-08 DOI: 10.1002/itl2.70107

Yin Gao

{"title":"Safety Fault Prediction and Diagnosis of Power Measurement Equipment Based on 6G Big Data Analysis","authors":"Yin Gao","doi":"10.1002/itl2.70107","DOIUrl":"https://doi.org/10.1002/itl2.70107","url":null,"abstract":"<div>\u0000 \u0000 <p>The advent of 6G networks has revolutionized power system monitoring by enabling ultra-fast, low-latency communication, which is essential for real-time fault prediction and diagnosis in power measurement equipment. However, conventional fault diagnostic methods often rely on centralized data processing, which raises significant concerns about data privacy threats, latency, and inefficiencies in real-time problem identification. We provide a Big Data-Driven Predictive Analytics with Federated Learning (BD-PA-FL) platform to address these issues. Without sending sensitive raw data, this novel method enables decentralized, privacy-preserving model training across numerous edge devices. By utilizing distributed big data and safeguarding data privacy, BD-PA-FL enables decentralized predictive analytics through FL. It avoids centralized data pooling, which lowers latency and improves real-time, privacy-aware fault detection in contrast to traditional fault diagnosis. To enable effective and intelligent fault prediction at the network edge, the proposed framework incorporates several essential elements. First, vital operating metrics from power equipment are captured by real-time sensor data collection. After that, insightful feature extraction methods are employed to identify significant patterns in the unprocessed data, enabling the detection of anomalies at an early stage. FL algorithms allow the system to collaboratively train predictive models across distributed nodes without sharing sensitive data, preserving privacy. By leveraging a cloud-edge AI architecture, the system ensures scalability, low latency, and effective resource utilization for predictive maintenance. Experimental results confirm that the BD-PA-FL framework significantly improves fault detection accuracy, reduces downtime, and enhances overall grid reliability in a secure, 6G-enabled environment.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 5","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145012330","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

LLM-Enhanced PSO for ECU Configuration in Wireless-Supported Distribution Network Self-Restoration 无线配电网自恢复中ECU配置的llm增强粒子群算法

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Internet Technology Letters Pub Date : 2025-09-08 DOI: 10.1002/itl2.70135

Hongtao Mao, Yifeng Wang, Bin Dong, Yangyang Miao, Wu Ma, Jun Wang

引用次数: 0

Effective Centralized Power Control and Management of Nano-Grid Using DT Based Novel Distributed Framework 基于DT的新型分布式框架对纳米电网的有效集中功率控制与管理

IF 0.5

Internet Technology Letters Pub Date : 2025-09-05 DOI: 10.1002/itl2.70080

Jarabala Ranga, Gopinath Palai, Rabi N. Satpathy

{"title":"Effective Centralized Power Control and Management of Nano-Grid Using DT Based Novel Distributed Framework","authors":"Jarabala Ranga, Gopinath Palai, Rabi N. Satpathy","doi":"10.1002/itl2.70080","DOIUrl":"https://doi.org/10.1002/itl2.70080","url":null,"abstract":"<div>\u0000 \u0000 <p>Nano-grid is an independent hybrid sustainable framework which uses both renewable and non-renewable power sources to continuously supply energy to load. Nano-grid finds its possibilities for the integration of distributed energy sources for realizing versatile and efficient energy management systems for future homes, local communities, and buildings. Nano-grid's energy trading system effectiveness might depend on various factors including core efficient management components such as energy storage systems (ESS) and renewable energy devices. Smart advanced functions in consumer devices and their unpredictable usage patterns result in unpredictable fluctuations in consumption of power. These fluctuations pose significant challenges in stability and quality of the power rid and create complex power imbalance issues which become harder to control and manage. Innovative power control and management models are essential to solve these issues in the nano-grid. In recent times, machine learning algorithms can be used to predict, track the current conditions, and make appropriate adjustments to the quality settings of power. In this research, effective centralized power control and management of the nano-grid using DT-based novel distributed framework is presented. This system utilizes a novel distributed framework based on a decision tree to enhance the agility and stability of complex and large-scale power systems. Performance measures like accuracy, F1-score, and RMSE are used to evaluate the performance of this system. This system will achieve better centralized power control and management.</p>\u0000 </div>","PeriodicalId":100725,"journal":{"name":"Internet Technology Letters","volume":"8 5","pages":""},"PeriodicalIF":0.5,"publicationDate":"2025-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144998946","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

Enhancing Car Tracking Systems With DNN-LoRa 用DNN-LoRa增强汽车跟踪系统

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Internet Technology Letters Pub Date : 2025-09-04 DOI: 10.1002/itl2.70130

Malak Abid Ali Khan, Senlin Luo

引用次数: 0