Transactions on Emerging Telecommunications Technologies最新文献

{"title":"Development of a Genetic Algorithm for Optimal Response Time Based on Full Scheduling Model of Electric Vehicle","authors":"Zouhaira Abdellaoui,&nbsp;Houda Meddeb","doi":"10.1002/ett.70152","DOIUrl":"https://doi.org/10.1002/ett.70152","url":null,"abstract":"<div>\u0000 \u0000 <p>Genetic algorithms (GAs) are frequently used in the design of electric vehicles to optimize various parameters, including battery capacity, motor size, and vehicle weight since they offer a powerful tool for improving their performance. In this paper, we focused our interest on the development of GA in the context of optimizing the response time based on the full scheduling model of electric vehicles applied to a modern vehicle of the Society of Automotive Engineers (SAE) Benchmark. The framework design is a set of many nodes connected through the Real-Time protocol FlexRay and the middleware Data Distribution Service (DDS). GA is implemented to find the optimal set of parameters that minimize the response time required for the static scheduling method applied to a SAE Benchmark application. This approach allows one to take advantage of FlexRay network high speed and to profit from DDS Quality-of-Service (QoS) management in the context of automotive electrical systems. Performance evaluations will be conducted to prove the efficiency, reliability, and robustness of GA proposed in this framework, and a comparison with other algorithms is discussed.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930324","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":"CSI Estimation for IRS-Assisted Massive MIMO Wireless Communication Systems: A Low Complexity Greedy Pursuit Approach","authors":"Mohammad Javad Azizipour","doi":"10.1002/ett.70150","DOIUrl":"https://doi.org/10.1002/ett.70150","url":null,"abstract":"<div>\u0000 \u0000 <p>The future wireless networks are capable of responding to the huge demand for connectivity if they employ the new technologies in physical and network layers. The intelligent reflecting surface (IRS) is an emerging technology introduced for the physical layer of such networks. It fairly controls the multipath environment by reflecting or transmitting the signal, thereby alleviating the problem of signal blockage, specifically in millimeter wave (mm-wave) systems. However, channel state information (CSI) estimation is one of the fundamental challenges of IRS technology when it operates in passive mode. In this paper, we propose a new greedy algorithm to estimate the uplink cascade channel between the base station (BS), IRS, and users. This algorithm utilizes the inherent spare property of the channel and divides it into two general forms, that is, row and column sparsity, searches for the location of the whole non-zero coefficients in the rows, and then refines the locations by identifying the non-zero ones in the columns. Finally, the coefficient values are calculated by solving a simple least square problem. The simulation results demonstrate that the proposed approach substantially outperforms state-of-the-art algorithms regarding computational complexity, pilot compression rate, and mean square error.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930323","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":"Enhancing Deep Learning-Based Channel Estimation: A Novel Autoencoder-Based Approach","authors":"Ephrem Fola,&nbsp;Chunbo Luo,&nbsp;Yang Luo,&nbsp;Xiangyuan Jiang","doi":"10.1002/ett.70148","DOIUrl":"https://doi.org/10.1002/ett.70148","url":null,"abstract":"<div>\u0000 \u0000 <p>Deep-learning (DL) methods have shown promising performance in pioneering studies on orthogonal frequency division multiplexing (OFDM) channel estimation challenges. Unlike typical DL-based channel estimation methods that mainly rely on separate real and imaginary inputs while ignoring the inherent correlation between the two streams, this paper proposes AE-DENet, a novel autoencoder (AE)-based data enhancement network to achieve robust channel estimation for OFDM systems. AE-DENet employs the classic least square (LS) channel estimation as input and proposes a data enhancement method to extract the interaction features from the real and imaginary parts of the complex channel estimation matrix, which are joined with the original real and imaginary streams to generate an enhanced input for better channel inference. Experimental findings in terms of the mean square error (MSE) results for a range of representative DL-based channel estimation methods demonstrate that the proposed AE-DENet-enhanced channel estimation framework achieves state-of-the-art channel estimation performance with trivial added computational complexity. Furthermore, the input dimensions of the DL-based channel estimation models can be adaptively adjusted to accommodate the dimension of the enhanced LS input. The proposed approach is also shown to be robust to channel variations and high user mobility.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143914126","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":"Implementation of Hybrid Wild Geese Migration-Bird Swarm Algorithm-Based Optimal Power Allocation Strategy for Spectral Efficiency Analysis in Massive MIMO System","authors":"Swathi Jallu,&nbsp;K. Padma Raju","doi":"10.1002/ett.70153","DOIUrl":"https://doi.org/10.1002/ett.70153","url":null,"abstract":"<div>\u0000 \u0000 <p>Spectral Efficiency (SE) plays a crucial role in designing and transmitting the amount of data in wireless communication systems that is an important measure for validating the effectiveness of cellular systems. It determines the usage of a limited frequency spectrum, but it fails to measure consumed power. Numerous methods have been developed to analyze the Multiple-Input Multiple-Output (MIMO) system with diverse channel methods. This MIMO system effectively enhances the data throughput, and it can serve diverse users simultaneously within the same frequency band. It significantly enhances the system framework and minimizes the impact of signal fading. However, the MIMO system faces challenges like lower transmit power, maximized coverage space, higher spectral efficiency, and multiplexing gain. To solve these issues, a novel optimization algorithm is developed in massive Multi-User MIMO (MU-MIMO) for maximizing SE in a Downlink (DL) system. This DL communication system is utilized to determine the complex channel conditions among the Base Station (BS) and user equipment. Also, it provides better data transmission control, and it carefully manages the signal strength in the MIMO system. Here, many antennas are provided in BS to distribute individual antenna consumers at the same time in a similar frequency band, and the duplex mode time division uses the beamforming training scheme. An optimal resource allocation together determines the DL transmission signal power training, Uplink (UL) transmission signal power training, UL transmission training duration, and DL transmission to increase the SE, data signal power initiated from the complete given energy budget. Since SE is the main concern of this work, this paper implements an efficient heuristic mechanism for increasing SE in a Massive MIMO (M-MIMO) method. The M-MIMO system accurately provides the best cell edge coverage and maximizes network capacity. It achieves better spectral efficiency to enhance overall throughput performance. It has the ability to focus signals by developing a new model for better signal quality and neglects interferences in the network environment. Here, the hybrid optimization algorithm Integrating the Position of Wild Geese Migration Optimization Algorithm (WGMO) and Bird Swarm Algorithm (BSA) named as IPWGBS is implemented to perform the ideal Power Allocation (PA) for the end users in BSs. The IPWGBS algorithm effectively handles and solves large-scale optimization issues to reduce the risk of getting stuck in local optima. The computational complexity is analyzed through valid simulations for the developed optimal PA mechanism. The experiments demonstrate that the developed model provides enhanced SE with optimal resource allocation compared to previous works. From the statistical analysis, the overall performance of the designed model shows 3.6% ROA, 3.8% GTO, 3.0% GMO, and 4.0% BSA in terms of the best measure.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143914127","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":"Hybrid Optimization for IRS-Aided Secure Communication: A Gradient Projection and Dynamic Security Framework","authors":"S. Sivasankar,&nbsp;S. Markkandan","doi":"10.1002/ett.70149","DOIUrl":"https://doi.org/10.1002/ett.70149","url":null,"abstract":"<div>\u0000 \u0000 <p>The emergence of advanced wireless communication technologies has heightened the need for effective physical-layer security, particularly in multi-user environments susceptible to eavesdropping. In this work, we propose a Hybrid Gradient Descent Optimization (HGDO) framework that leverages an Intelligent Reflecting Surface (IRS) to safeguard wireless transmissions. Our methodology features a hierarchical two-phase design, a Gradient Projection Method that jointly refines beamforming vectors and IRS phase shifts, and a Dynamic Security Region Expansion (DSRE) algorithm that reacts in real time to shifts in channel conditions. Simulation results confirm that the HGDO framework achieves notable improvements in secrecy rates, energy efficiency, and adaptability under diverse system settings. For instance, with 100 IRS elements, the solution attains a secrecy rate of 42 bps/Hz, showcasing its scalability and reliability. These findings suggest that HGDO holds strong promise for fortifying next-generation wireless networks against emerging security threats.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143901105","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":"Secure Content Protection and Verification Framework for Digital Images Communication","authors":"Osama S. Faragallah,&nbsp;Walid El-Shafai,&nbsp;Osama Elshakankiry,&nbsp;Ashraf Afifi,&nbsp;Hala S. El-sayed","doi":"10.1002/ett.70131","DOIUrl":"https://doi.org/10.1002/ett.70131","url":null,"abstract":"<div>\u0000 \u0000 <p>Data security is an urgent and important dilemma in recent times because of the fast growth of the Internet and multimedia applications. Steganography, watermarking, and encryption techniques may be utilized to achieve data robustness and confidentiality. In this paper, the content-based image verification and data integrity technique are introduced. This technique is reliable and appropriate for confirming the reliability of images communicated through unreliable channels. First, the transferred image is divided into a number of dedicated blocks with different block sizes. Then, several discrete transformations like the DFT (Discrete Fourier Transforms), DWT (Discrete Wavelet Transform), and DCT (Discrete Cosine Transform) are employed and tested individually. They are utilized to insert a block-based watermark for every image block in an alternative image block corresponding to a certain mechanism. The marked image is transmitted over a wireless channel with various corruptions and attacks. On the receiver side, the embedded watermarks for each image block are obtained to distinguish dubious falsification behaviors. Various image analyses and comparisons are employed to test and examine the reliability of the proposed technique to accomplish superior content verification and safeguard images communicated over vulnerable transmission networks. Assessment findings approve the rightness of the suggested technique for different multimedia applications with confidential information categories like military services. In addition, comparative experimental findings and results demonstrate that the suggested content-based image verification and data integrity technique applying the DFT is the best protection framework contrasted with the DWT and DCT, as it achieves in the case of the Peppers image a low MSE of 6.1787, high PSNR of 46.2765 dB, and high C_r of 0.9933 at a 4 × 4 block size. These achievements ensure and confirm that the proposed method is an effective methodology for multimedia integrity and validation applications.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143896960","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":"Hybrid Secure Onlooker: Enabling End-to-End Security for Cloud Data Center by Hybrid VM Segmentation","authors":"Saravanan Kumarasamy,&nbsp;Santhosh Rajendran","doi":"10.1002/ett.70136","DOIUrl":"https://doi.org/10.1002/ett.70136","url":null,"abstract":"<div>\u0000 \u0000 <p>Cloud computing is an innovative technology that provides computing services over the internet and replaces the requirement to own physical hardware or software. Security threats present a wide range of risks to cloud computing, and a security threat defense plays a significant role in cloud computing. Virtual machines (VM) serve as the backbone, providing flexible and scalable resources for running and storing data. Moving Target Defense (MTD) and Blockchain enhance security and privacy by reducing the chances of successful attacks and minimizing the impact of security attacks. To address these issues, we propose integrating MTD and blockchain technologies within the cloud computing environment named Hybrid Secure Onlooker (HSO). The proposed work involves several entities, including Cloud Users (CUs), Centralized Subnet Manager (CSM), Distributed Group Manager (DGM), Consortium Block Module (CBM) and Private Block Module (PBM). Initially, we perform Multi-Factor Authentication (MFA) to establish secure communication and to avoid malicious traffic. Followed by this, we utilize the Komoda Miliphir optimization (KMO) algorithm to perform CUs' task scheduling based upon the task types, task sensitivity, and task size. Entrenched in the scheduled tasks, the CSM performs classification and grouping of cloud VMs, assigning them to their capacity, security protocols, and availability, utilizing the Residual Flowed Capsule Network (RFC-Net). The grouped subsets are overseen and managed by the DGM, which handles MTD operations such as virtual switch placement and VM migration within the subsets. Finally, the transactions are stored in the hybrid blockchain layer with CBM and PBM to ensure privacy and security. The is the implementation tool for realizing the proposed HSO model. The proposed model can be examined based on several metrics with state-of-the-art work comparisons. The results show that the proposed HSO model outperforms the state-of-the-art models.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892829","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":"IoT Data Transmission Security Using Blockchain With a Trust-Weighted Proof of Authority Consensus Mechanism in Healthcare","authors":"Shatakshi Kokate,&nbsp;Urmila Shrawankar","doi":"10.1002/ett.70139","DOIUrl":"https://doi.org/10.1002/ett.70139","url":null,"abstract":"<div>\u0000 \u0000 <p>Healthcare systems generate vast amounts of sensitive data, and ensuring its security and privacy remains a significant challenge. Various traditional solutions, including encryption techniques, access control mechanisms, and centralized cloud-based systems, have been developed to address these issues. However, these approaches often face challenges such as single points of failure, limited scalability, and lack of decentralized trust management. Encryption schemes such as AES and RSA are computationally expensive and do not inherently address issues of data integrity or transparency. At the same time, centralized systems are prone to security breaches and third-party vulnerabilities. This paper proposes a blockchain-based solution with a trust-weighted proof of authority (PoA) consensus mechanism to overcome these limitations and ensure secure data transmission in the Internet of Things (IoT)-enabled healthcare systems. The Density-based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is employed for healthcare data classification, followed by Huffman encoding for data compression. Data are encrypted using a combination of the Substitution-Caesar cipher and Updated Elliptical Curve Cryptography (UECC). A novel trust-weighted PoA consensus mechanism is then used for block validation, enhancing the security of data transmission. The proposed solution achieves an accuracy of 99.38%, an F1 score of 98.2%, a precision of 98.5%, a recall of 98%, a throughput of 65 Mbps, a latency of 0.23 s, and a processing time of 17 s. The results demonstrate that the blockchain-based solution effectively addresses the shortcomings of traditional methods, ensuring higher security, scalability, and trust in healthcare data management.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143892830","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":"A Novel LC-LOA and S3R2GCNN-Based Dynamic Workflow Process Type Identification and Scheduling in Cloud","authors":"Sai Sathish Kethu,&nbsp;Dharma Teja Valivarthi,&nbsp;Sreekar Peddi,&nbsp;Swapna Narla,&nbsp;Durai Rajesh Natarajan,&nbsp;N. Purandhar","doi":"10.1002/ett.70129","DOIUrl":"https://doi.org/10.1002/ett.70129","url":null,"abstract":"<div>\u0000 \u0000 <p>Workflow scheduling (WS) maps out the processes and manages the execution of interdependent works within a process. However, the existing studies did not identify the workflow process types for efficient WS. Therefore, this paper presents a novel LC-LOA and S3R2GCNN-based dynamic workflow process type identification and scheduling in the cloud. Primarily, the cloud users register and log in with the cloud server. Afterward, the user assigns the workflow, followed by attribute extraction. Subsequently, the hashcode is generated for attributes by using THA. Next, the workflow deduplication is checked. If the workflow is repeated, it is removed from the workflow pool; otherwise, the workflow is given for WPTIS. In WPTIS, the classifier is trained based on data acquisition, graph slicing, attribute extraction, feature extraction, feature selection by LC-LOA, process labeling by L-Fuzzy, and classification by S3R2GCNN. Also, the features are extracted from the cloud server and given to WS. Eventually, the workflow is scheduled by using the Linear Congruential Lyrebird Optimization Algorithm (LC-LOA). The results show that the proposed system obtained a high accuracy of 98.43%, outperforming conventional models.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143889013","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":"QDKFFHNet: Quantum Dilated Kronecker Feed Forward Harmonic Net for Intrusion Detection in IoT-Based Smart City Applications","authors":"Selvam Ravindran,&nbsp;Velliangiri Sarveshwaran","doi":"10.1002/ett.70141","DOIUrl":"https://doi.org/10.1002/ett.70141","url":null,"abstract":"<div>\u0000 \u0000 <p>In today's world, people are worried about keeping their information safe and secure. One essential way to keep safe is by employing a technique called intrusion detection (ID), which helps to find threats in networks while data is being sent. Deep learning (DL) aids the Internet of Things (IoT) and smart cities by creating devices that can think and make decisions on their own without human help. Hence, an effective approach named Quantum Dilated Kronecker Feed Forward Harmonic Net (QDKFFHNet) is introduced for ID in IoT-Based Smart City Applications. Initially, the system model is considered, and then, data collection is carried out. Thereafter, data normalization is conducted by linear normalization. After that, feature dimension transformation is conducted by information gain. Feature extraction is conducted. Moreover, feature conversion is conducted, and feature selection is performed by Mahalanobis distance and Wave-Hedges metric. Lastly, ID is done by employing QDKFFHNet, which is the combination of Quantum Dilated Convolutional Neural Network (QDCNN) and Deep Kronecker Network (DKN). It is noticed that QDKFFHNet has gained an accuracy of 92.69%, a negative predictive value (NPV) of 86.73%, a specificity of 91.77%, a sensitivity of 92.79%, and a positive predictive value (PPV) of 92.60%.</p>\u0000 </div>","PeriodicalId":23282,"journal":{"name":"Transactions on Emerging Telecommunications Technologies","volume":"36 5","pages":""},"PeriodicalIF":2.5,"publicationDate":"2025-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143888886","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}