Transactions on Emerging Telecommunications Technologies最新文献_第6页

Beidou-Enhanced Sparse Variational GNSS/INS Integration for Sub-5 cm Smart Sugarcane Farming 5厘米以下智能甘蔗种植的北斗增强稀疏变分GNSS/INS集成

IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-06-07 DOI: 10.1002/ett.70457

Yongsheng Xie

{"title":"Beidou-Enhanced Sparse Variational GNSS/INS Integration for Sub-5 cm Smart Sugarcane Farming","authors":"Yongsheng Xie","doi":"10.1002/ett.70457","DOIUrl":"https://doi.org/10.1002/ett.70457","url":null,"abstract":"<div>\u0000 \u0000 <p>We propose a Beidou-augmented Sparse Variational GNSS/INS Combined System (BSV-GIIS) to tackle the difficulties of high-accuracy positioning in intelligent sugarcane agriculture, where thick vegetation and multipath interference reduce the effectiveness of traditional tightly coupled Kalman filter (TCKF) approaches. The system introduces a hierarchical sparse approximate message passing (HSAMP) framework, which reformulates the fusion problem into a two-layer variational inference process with adaptive sparsity constraints, thereby capturing the inherent noise sparsity in agricultural environments. At the global scale, a mixture of sparse Gaussians approximates the posterior state distribution, whereas the local scale improves estimates by modeling Beidou-specific residuals with heavy-tailed distributions. In addition, a compact hybrid Kalman-variational filter (LHKVF) processes inertial data by means of selective Mahalanobis gating, which permits effective outlier rejection. The 5 cm accuracy is based on median performance at nominal conditions, while RMS errors in dense canopy environments are above 8 cm. This shows that although the median error values are within the 5 cm range for open and partial canopies, the RMS errors increase to 8.3 cm in dense canopies, thus proving the limitation of sparse assumptions in dense foliage occlusions. This shows that although the system attains centimeter-level accuracy in nominal situations, there is a performance degradation in dense foliage occlusions. Implemented on a Xilinx Versal ACAP, BSV-GIIS shows effective handling of sparse matrix computations and precise coordination between IMU and GNSS data flows. Experimental outcomes establish its advantage in accuracy and processing speed, which renders it a feasible option for embedded systems with limited resources in precision agriculture.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"37 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148237586","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Joint Channel Modeling, Parameter Estimation and Geometry-Based Indoor Localization for 5G Systems 5G系统联合信道建模、参数估计和几何室内定位

IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-06-02 DOI: 10.1002/ett.70456

Paulo Francisco da Conceição, Rodrigo Pinto Lemos, Flávio Geraldo Coelho Rocha

{"title":"A Joint Channel Modeling, Parameter Estimation and Geometry-Based Indoor Localization for 5G Systems","authors":"Paulo Francisco da Conceição, Rodrigo Pinto Lemos, Flávio Geraldo Coelho Rocha","doi":"10.1002/ett.70456","DOIUrl":"https://doi.org/10.1002/ett.70456","url":null,"abstract":"<p>This work proposes a Mobile Station (MS) localization method for indoor environments using a single Base Station (BS) equipped with a massive Multiple-Input Multiple-Output (mMIMO) antenna array. The proposal can be divided into three main stages: (1) channel modeling, (2) estimation of localization parameters, and (3) estimation of MS position. We consider a millimeter-Wave (mmWave) mMIMO channel model to estimate five localization parameters: Time of Arrival (ToA), two-dimensional Angle of Departure (2D-AoD)-azimuth and elevation, and two-dimensional Angle of Arrival (2D-AoA)-azimuth and elevation. Then, from AoA and AoD data, the proposed method can analyze the various transmission paths and identify whether there is a Line-of-Sight (LoS) path, allowing the automatic determination and application of the most suitable localization algorithm. The system model is comprehensive, approaching a 5G small cell with mmWave and mMIMO technologies transmitting in an indoor environment with LoS and Non-Line-of-Sight (NLoS) conditions and multiple Scatterers. Simulations are carried out, and the results are compared to those of three related methods present in the literature. The obtained results demonstrate that the proposed method achieves sub-metric accuracy under LoS conditions and outperforms related methods in NLoS conditions. Additionally, the proposed method is simpler, faster, and relies on a single BS for localization.</p>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"37 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ett.70456","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148173807","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Cascaded Deep Ensemble Learning for Position Integrity Assessment in Vehicular Ad Hoc Networks 基于级联深度集成学习的车载Ad Hoc网络位置完整性评估

IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-29 DOI: 10.1002/ett.70453

A. Anushya, Mohammad Alsaffar, Meiad Jrad Aljrad, Asmaa Alrayzah, Rasha Almarshdi, Bedour Alrashidi, Abrar Alamr, Badria Abaker Ibrahim Mohajir

{"title":"Cascaded Deep Ensemble Learning for Position Integrity Assessment in Vehicular Ad Hoc Networks","authors":"A. Anushya, Mohammad Alsaffar, Meiad Jrad Aljrad, Asmaa Alrayzah, Rasha Almarshdi, Bedour Alrashidi, Abrar Alamr, Badria Abaker Ibrahim Mohajir","doi":"10.1002/ett.70453","DOIUrl":"https://doi.org/10.1002/ett.70453","url":null,"abstract":"<div>\u0000 \u0000 <p>Position integrity is a critical requirement for the safe operation of vehicles in Intelligent Transportation Systems (ITS). Manipulated position messages lead to unsafe decisions and traffic confusion and create possible accidents. Existing approaches primarily focus on improving localisation accuracy and securing vehicle identities, rather than detecting false positional behaviors. Also, real-world communication challenges make integrity verification more difficult in dense vehicular environments. To address these challenges, we propose a Cascaded-Deep Ensemble Learning (CADE) model to assess positional integrity in VANET environments. The CADE model evaluates the trust of shared position information using a multi-stage pipeline. It combines motion-prediction-based Position Error (PE) estimation, adaptive safety-bound evaluation via Adaptive Dynamic Level (ADL), temporal-behavior verification using Temporal Consistency Score (TCS), and cooperative validation via Cooperative Plausibility Index (CPI). These integrity indicators are fused and evaluated using lightweight ensemble classifiers to obtain the position information of active vehicles. The proposed CADE framework is evaluated on the VeReMi dataset; experimental results show that the approach achieves a high detection accuracy of 99.50% and demonstrates a strong ability to identify false-position attacks even under congested vehicular communication conditions.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"37 6","pages":""},"PeriodicalIF":2.5,"publicationDate":"2026-05-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148167053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-26

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-25

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-22

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-20

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-18

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IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-18

引用次数: 0

IF 2.5 4区计算机科学

Transactions on Emerging Telecommunications Technologies Pub Date : 2026-05-18

引用次数: 0