Transactions on Emerging Telecommunications Technologies最新文献

{"title":"Correction to “Energy Efficient Resource Allocation in Cache-Enabled Fog Networks”","authors":"","doi":"10.1002/ett.70072","DOIUrl":"https://doi.org/10.1002/ett.70072","url":null,"abstract":"<p>R. Basir, S. Qaisar, M. Ali, M. Naeem, and A. Anpalagan, “Energy Efficient Resource Allocation in Cache-Enabled Fog Networks,” <i>Transactions on Emerging Telecommunications Technologies</i> 32, no. 11 (2021): e4343, https://doi.org/10.1002/ett.4343.</p><p>On page 1, the order of affiliation of author Saad Qaisar is incorrect and should be in reverse order. First affiliation of author Saad Qaisar be read as: Department of Electrical and Electronic Engineering, University of Jeddah, Jeddah, Kingdom of Saudi Arabia and second affiliation as: School of Electrical Engineering and Computer Science, National University of Science and Technology, Islamabad, Pakistan.</p><p>On page 15, paragraph 1 of Acknowledgments section, the grant order of acknowledgment and statement of acknowledgment are incorrect. Page 15, acknowledgments section paragraph 1 should be read as: This work is supported by following: 1. University of Jeddah Deanship of Scientific Research grant UJ-20-017-DR. 2. Pakistan Higher Education Commission research grant number IV-/PERIDOT/R&amp;D/HEC/2020/Sept 09 2020.</p><p>The online version of the article has also been updated.</p><p>We apologize for this error.</p>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/ett.70072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380037","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}

{"title":"A Novel Approach to Driver Negligence Detection: EAXB-EVS Algorithm With IoT Integration","authors":"Bharathi S,&nbsp;P. Durgadevi","doi":"10.1002/ett.70068","DOIUrl":"https://doi.org/10.1002/ett.70068","url":null,"abstract":"<div>\u0000 \u0000 <p>In recent days, road accidents have become a major issue, caused by negligence of the driver such as drowsiness, alcohol consumption during driving, gas leakage, tiredness, and traffic law violations. Timely decisions and accurate driver negligence detection are mandatory for avoiding road accidents and fatalities. However, the earlier research encountered various obstacles such as more energy consumption, poor detection performance, and required high computational time. This research proposes a novel Internet of Things-based Ensemble-voting Adaptive Extreme Boost-based Energy Valley Search algorithm within the Vehicular Ad-Hoc Networks environment for early and accurate detection of driver negligence. The proposed Ensemble-voting Adaptive Extreme Boost-based Energy Valley Search framework utilizes an Eye Aspect Ratio and Mouth Aspect Ratio analysis to identify the driver's facial contours like mouth and pupils by analyzing the imaging data. Further, the Ensemble-voting Adaptive Extreme Boost model is employed for effective prediction of driver negligence that combines the weak learner models using ensemble voting and adapts dynamically for identifying the driver's state of carelessness including intoxication, gas leakage, and drowsiness. The hyperparameter of the Ensemble-voting Adaptive Extreme Boost framework is fine-tuned by applying Energy Valley Search, which enhances the accuracy and efficiency of the system while minimizing the computational overhead and energy consumption. The effectiveness of the proposed model is validated using some evaluation measures on three datasets namely, the Driver Inattention Detection Dataset, the India Road Accident Dataset, and the Driver Drowsiness Dataset. The simulation outcomes indicate that the Ensemble-voting Adaptive Extreme Boost-based Energy Valley Search framework attained a higher accuracy of 98.87%, less execution time of 1.03 s, and less energy usage of 5%, which makes the proposed system highly efficient for the real-time vehicular network application.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380370","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}

{"title":"Channel Estimation Based Intelligent Reflecting Surfaces for Massive MIMO System Considering Spatially Correlated Channels","authors":"Jamal Amadid,&nbsp;Asma Khabba,&nbsp;Zakaria El Ouadi,&nbsp;Abdelouhab Zeroual","doi":"10.1002/ett.70066","DOIUrl":"https://doi.org/10.1002/ett.70066","url":null,"abstract":"<div>\u0000 \u0000 <p>Recently, many fundamental technologies have emerged to boost and improve the performance of existing and future wireless communication systems, one of these technologies being the utilization of intelligent reflecting surfaces (IRS). This work investigates the channel estimation and spectral efficiency (SE) of a Massive multiple-input multiple-output (M-MIMO) system based on an IRS for spatially correlated channels. The system's performance is evaluated in terms of both channel estimation and SE, utilizing the minimum mean square error (MMSE) estimator. Accordingly, a three-stage M-MIMO channel estimation assisted by an IRS using the pilot sequences in a more practical propagation environment, that is, spatially correlated channels, wherein the IRS components empower the BS to estimate the uplink reflected channel state information (CSI) (i.e., estimation of reflected channels). In addition, the three stages channel estimate based on pilot sequences is computed and evaluated using the MMSE estimator and the normalized-mean square error (NMSE) metric, respectively. In this framework, this work proposes a local multiple scattering (LMS) model that describes the spatial correlation (SC) over the proposed uniform rectangular array (URA) by relying on the LMS model that describes the SC over a ULA configuration. In other words, using the Kronecker product (KP) of the correlation matrix constructed through a ULA, we built the correlation matrix that describes the SC over the proposed URA. In contrast to the linear array, the proposed array design is more constrained, leading to a higher degree of SC and better channel estimation quality. Numerical results are provided to assert and validate both our theoretical expression, as well as, the effectiveness of the proposed configuration.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143380495","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}

{"title":"Distributed Cooperative Spectrum Optimization Method Based on Coalition Formation Game for Ocean and Traffic Iot","authors":"Junzhe Li,&nbsp;Rong Wang,&nbsp;Yuan Huo,&nbsp;Wen Tian","doi":"10.1002/ett.70065","DOIUrl":"https://doi.org/10.1002/ett.70065","url":null,"abstract":"<div>\u0000 \u0000 <p>With the acceleration of globalization and the advent of rapid technological development, the advancement of Ocean Internet of Things (OIoT) and Traffic Internet of Things (TIoT) communications is of particular significance. However, the existing problems are the scarcity of spectrum resources at sea, the presence of malicious jamming from external sources, and mutual interference within the system itself for OIoT and TIoT systems. It is therefore crucial to enhance spectrum utilization for maritime users and shore-side traffic. To tackle this issue, we propose a distributed anti-jamming cooperative spectrum decision-making method based on a coalition formation game. Specifically, it achieves stable coalition grouping by optimizing coalition formation strategies, thereby increasing the transmission rate. Furthermore, we demonstrate that the proposed coalition formation game can reach the Nash equilibrium solution through the application of exact potential game theory. Our proposed method ensures the feasibility of spectrum optimization in dynamic environments. Compared with other coalition formation algorithms, our proposed algorithm reduces the number of iterations needed for convergence by 50%, thus guaranteeing real-time system performance. Finally, the results of our simulations indicate that our strategy outperforms existing approaches in terms of total rate performance.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362807","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}

{"title":"An Extensive Review of Machine Learning and Deep Learning Techniques on Network Intrusion Detection for IoT","authors":"Supongmen Walling,&nbsp;Sibesh Lodh","doi":"10.1002/ett.70064","DOIUrl":"https://doi.org/10.1002/ett.70064","url":null,"abstract":"<div>\u0000 \u0000 <p>The Internet of Things (IoT) has transformed technology interactions by connecting devices and facilitating information exchange. However, IoT's interconnectivity presents significant security challenges, including network security, device vulnerabilities, data confidentiality, and authentication. Many IoT devices lack strong security measures, making them susceptible to misuse. Additionally, privacy concerns arise due to sensitive data storage. Solutions such as secure authentication, encryption, and encrypted communication are vital. Intrusion detection systems (IDS) play a crucial role in proactively protecting networks, yet they encounter significant challenges in identifying new intrusions and minimizing false alarms. To tackle these issues, researchers have developed IDS systems that leverage machine learning (ML) and deep learning (DL) techniques. This survey article not only provides an in-depth analysis of current IoT IDS but also summarizes the techniques, deployment strategies, validation methods, and datasets commonly used in the development of these systems. A thorough analysis of modern Network Intrusion Detection System (NIDS) publications is also included, which evaluates, examines, and contrasts NIDS approaches in the context of the IoT with regard to its architecture, detection methods, and validation strategies, dangers that have been addressed, and deployed algorithms setting it apart from earlier surveys that predominantly concentrate on traditional systems. We concentrate on IoT NIDS implemented by ML and DL in this survey given that learning algorithms have an excellent track record for success in security and privacy. The study, in our opinion, will be beneficial for academic and industrial research in identifying IoT dangers and problems, in implementing their own NIDS and in proposing novel innovative techniques in an IoT context while taking IoT limits into consideration.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143248497","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}

{"title":"Optimal Beamforming for Covert Communication in MIMO Relay Systems","authors":"He Zhu,&nbsp;Huihui Wu,&nbsp;Yulong Shen,&nbsp;Xiaohong Jiang","doi":"10.1002/ett.70063","DOIUrl":"https://doi.org/10.1002/ett.70063","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper investigates the optimal beamforming design for covert communication in a multiple-input multiple-output (MIMO) relay system consisting of source, destination, relay and warden. For both scenarios when each transmitting node knows the perfect or partial warden's channel state information (CSI), we first develop theoretical models to depict the inherent relationship between the beamforming matrices at source/relay and end-to-end covert performance of the system regard the minimum detection error probability and covert capacity. Based on these models, we then formulate the optimal beamforming for covert capacity maximization under perfect and partial CSI as linear non-convex (LNC) and non-linear non-convex (NLNC) optimization problems, respectively. We then apply Lagrangian and Hadamard inequality methods to solve the LNC optimization problem to determine the closed-form expressions for the optimal beamforming matrices at source/relay, based on which a stochastic gradient descent algorithm is developed to evaluate the maximum covert capacity. For the complicated NLNC problem, we propose an efficient search algorithm based on S-procedure lemma and interior point methods to identify the optimal beamforming matrices to reach the maximum covert capacity. Finally, we provide extensive numerical results to illustrate the covert performance enhancement from adopting the optimal beamforming in MIMO relay systems.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111674","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}

{"title":"An Enhanced IOMT and Blockchain-Based Heart Disease Monitoring System Using BS-THA and OA-CNN","authors":"Mohanarangan Veerappermal Devarajan,&nbsp;Akhil Raj Gaius Yallamelli,&nbsp;Rama Krishna Mani Kanta Yalla,&nbsp;Vijaykumar Mamidala,&nbsp;Thirusubramanian Ganesan,&nbsp;Aceng Sambas","doi":"10.1002/ett.70055","DOIUrl":"https://doi.org/10.1002/ett.70055","url":null,"abstract":"<div>\u0000 \u0000 <p>The heart disease monitoring system is helpful for doctors to understand the overall heart health of patients by measuring the functions of the heart via IoMT devices. However, the existing studies did not consider the arrhythmias' consequences along with ECG and PCG to predict heart disease accurately. Therefore, this paper presents an enhanced IoMT and blockchain-based heart disease monitoring system using BS-THA and OA-CNN. The doctor and patient can initially register and log in to the system. At this point, the keys are generated for patients and doctors. After login, the data sensing is done, and the sensed data is uploaded to the IPFS. Next, the hashcode is generated and stored in the blockchain. In the meantime, MAC is created and verified for authentication. After verifying the MAC, the sensed data is given to the heart disease classification system, which is trained based on preprocessing, spectrum analysis, signal decomposition by PV-EMD, scalogram, and grayscale conversion, ECG and PCG wavelet components extraction, ECG wave intervals extraction, arrhythmia consequences, feature extraction by DPCA, feature selection, and classification. Finally, the proposed OA-CNN effectively classified heart disease. Thus, the results proved that the proposed methodology achieved a higher accuracy of 98.32%, which is better than the prevailing models.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143111251","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}

{"title":"Blockchain Empowered Quantum Safe Batch Aggregate Signature Algorithm for Authenticated Data Trading in Internet of Vehicles","authors":"Rahul Singh,&nbsp;Laxminarayan Das,&nbsp;Dharminder Chaudhary","doi":"10.1002/ett.70054","DOIUrl":"https://doi.org/10.1002/ett.70054","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper contains a quantum-safe and efficient blockchain-based data trading framework designed for the Internet of Vehicles (IoV). With the proliferation of connected vehicles, there is a growing need for quantum-safe and trustworthy data sharing among vehicles, roadside infrastructure, and service providers. Due to Shor's algorithm, most of the existing traditional authenticated data delivery algorithms supporting blockchain will not work. The proposed framework supports blockchain's decentralized nature to ensure the authenticity of data and its transparency while minimizing the computational overhead to suit the distributed IoV communication environment. We have designed a blockchain-based data trading framework for the IoV, utilizing practical Byzantine Fault Tolerance (pBFT) consensus to ensure authentic transactions. With respect to gaining consensus efficiency, the general Byzantine Fault Tolerant (BFT) framework uses an all-to-all message pattern to reach final decision block. To reduce the cost of communication complexity from <span></span><math></math> to <span></span><math></math>, aggregation of signatures has been used in the proposed blockchain consensus framework. Moreover, consensus mechanisms like Proof of Work (PoW) may not be applicable to IoV networking systems due to their comparatively high energy consumptions. This framework is scalable in terms of key generation time, and the storage complexity is less as compared to the storage complexity <span></span><math></math> of the non-aggregated signature methods. The proposed module lattice-based aggregation of signatures offers approximately 58% faster rate of reading the blocks with respect to existing techniques. The consensus process benefits significantly from the implementation of aggregated signatures and verification, resulting in average energy consumption between 1.8% and 6.4%.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143110842","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}

{"title":"LoRa Meets Artificial Intelligence to Optimize Indoor Networks for Static EDs","authors":"Malak Abid Ali Khan,&nbsp;Senlin Luo,&nbsp;Hongbin Ma,&nbsp;Amjad Iqbal","doi":"10.1002/ett.70060","DOIUrl":"https://doi.org/10.1002/ett.70060","url":null,"abstract":"<div>\u0000 \u0000 <p>The architectural design of the Indoor Internet of Things (IIoT) network targeting static end devices (EDs) and gateways (GWs) has been innovatively formulated in this paper, integrating LoRa technology to mitigate losses and ensure seamless information reception through meticulous ED allocation. The arrangement of simultaneously transmitted data within the network server (NS) employs a deep neural network (DNN) with distributed machine learning (DML) to adjust transmission parameters, ensuring frequent uninterrupted bidirectional communication. This augmentation is obtained by strategically deploying EDs within distinct clusters determined by K-means and density-based spatial clustering with noise (DBSCAN), thus optimizing spreading factor (SF) and data rate (DR) allocation to prevent data congestion and improve signal-to-interference noise ratio (SINR). The proposed hybrid model (DR|SF) for pure and slotted ALOHA amplifies the network's performance metrics for indoor scenarios. A unified framework utilizing a one-slope model estimates path losses (PL) while exploring various bandwidths (BW), bidirectional interrogations, and duty cycles (DC) to lower the saturation and prolong the active lifespan of the EDs. The results manifest a packet rejection rate (PRR) of 0% for the DBSCAN, contrasting a 4.7% estimate for the K-means. The network saturation is minimized to 9.5% and 10.1%, correspondingly, significantly increasing the efficiency of slotted ALOHA (91%) and pure ALOHA (90.6%), thereby prolonging the longevity of EDs.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121213","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}

{"title":"Beyond Traditional RFID: Unveiling the Potential of Wi-Fi, 5G, Bluetooth, and Zigbee for Backscatter Systems","authors":"Sara El Mattar,&nbsp;Abdennaceur Baghdad","doi":"10.1002/ett.70062","DOIUrl":"https://doi.org/10.1002/ett.70062","url":null,"abstract":"<div>\u0000 \u0000 <p>Traditional RFID systems rely on dedicated readers, often expensive and bulky, hindering their widespread deployment. This paper proposes an alternative RFID system that leverages ubiquitous radio sources—Wi-Fi, 5G, Bluetooth, and Zigbee—to replace dedicated readers. Our system employs backscatter communication, where RFID tags modulate reflected signals from these readily available sources to transmit data. We investigate the feasibility and performance of this approach through Matlab simulator. Our results show that 802.11ax at 2.45 GHz exhibits the best symbol error rate, followed by 802.11n at the same frequency. However, 5G, Bluetooth, and Zigbee signals demonstrate lower performance even at high signal-to-noise ratios. To address this, we introduce error correction coding techniques (BCH and RS) that significantly improve communication reliability. Utilizing these codes, our system achieves a communication range of up to 1 m. This finding highlights the potential of ubiquitous radio sources as a viable alternative to dedicated RFID readers, opening doors for various applications.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 2","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-01-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143121215","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}