International Journal of Communication Systems最新文献

{"title":"Utility-Aware Network Slicing for Optimal Cell Planning in Emergency Scenarios","authors":"Sanjoy Debnath,&nbsp;Wasim Arif,&nbsp;Amit Baran Dey","doi":"10.1002/dac.70574","DOIUrl":"https://doi.org/10.1002/dac.70574","url":null,"abstract":"<div>\u0000 \u0000 <p>Content-based network slicing is a key technology to enable the transition from the network as infrastructure to network-as-services and offer services to business verticals. Its efficient use of limited network resources makes it a promising future wireless technique. This article presents a novel network slicing–based model for optimal cell planning while maximizing the content-based fairness utility. The users are divided in two categories: (i) emergency users (EUs) and (ii) normal users (NUs). Here, emergency services are limited to text and voice to prevent congestion, whereas NUs have access to all services (text, voice, and video). Both user types are considered across two emergency scenarios: zone-specific and random. Random EUs are those needing medical, safety, or security assistance, whereas zone-specific EUs are users within a disaster-affected area. Simulations are performed to observe the trade-off between the NU and EU association with the optimal BS while satisfying the demanded rate of service. The effectiveness of the proposed hybrid Dragonfly Algorithm with Differential Evolution (DADE) and Buyer Inspired Meta-heuristic Algorithm (BIMA) with Fuzzy C-means algorithm is demonstrated using simulation results. Comparative simulations show that the proposed DADE-based algorithm significantly outperforms other state-of-the-art algorithms in maximizing network utility.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615528","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":"Improving RIS-Aided CNOMA System Performance Under (\u0000 \u0000 \u0000 α\u0000 −\u0000 μ\u0000 \u0000 $$ alpha -mu $$\u0000 ) Fading Channels With CSI Uncertainty","authors":"M. Ramadevi,&nbsp;S. Anuradha,&nbsp;L. PadmaSree","doi":"10.1002/dac.70560","DOIUrl":"https://doi.org/10.1002/dac.70560","url":null,"abstract":"<div>\u0000 \u0000 <p>The cooperative non-orthogonal multiple access (CNOMA) system illustrates a prospective multiple access approach for future wireless communications. Line-of-sight communication is becoming more difficult to meet the needs of a modern society. As a result, reconfigurable intelligent surfaces (RIS) technology has emerged in proposed system. Consequently, this technology improves the efficiency of conventional CNOMA system by including RIS components. Efficiency of proposed RIS-aided CNOMA system is assessed using (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>α</mi>\u0000 <mo>−</mo>\u0000 <mi>μ</mi>\u0000 </mrow>\u0000 <annotation>$$ alpha -mu $$</annotation>\u0000 </semantics></math>) generalized fading channel. The evaluation is carried out with different fading elements including nonlinearity (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>α</mi>\u0000 </mrow>\u0000 <annotation>$$ alpha $$</annotation>\u0000 </semantics></math>) and multipath clusters (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>μ</mi>\u0000 </mrow>\u0000 <annotation>$$ mu $$</annotation>\u0000 </semantics></math>). The current research specifies the performance of proposed system with one-sided Gaussian, Rayleigh, Nakagami, and Weibull generalized fading channels for different fading components. The evaluation explores the effect of perfect and imperfect channel state conditions on proposed system through simulation results. Finally, the obtained results of the proposed RIS-Aided CNOMA system are compared with the traditional CNOMA system under (<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>α</mi>\u0000 <mo>−</mo>\u0000 <mi>μ</mi>\u0000 </mrow>\u0000 <annotation>$$ alpha -mu $$</annotation>\u0000 </semantics></math>) fading channels. The findings demonstrate that the significance of RIS technology to improve the efficiency of traditional CNOMA system in terms of ergodic capacity, bit error rate, and outage probability with the channel state information. Monte Carlo simulation is used for the simulation to get the accurate results.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615683","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":"Advanced Distance Estimation in ESP32-S2 IoT Devices Using Machine Learning-Enhanced FTM","authors":"Limin Hou","doi":"10.1002/dac.70573","DOIUrl":"https://doi.org/10.1002/dac.70573","url":null,"abstract":"<div>\u0000 \u0000 <p>Accurate distance estimation based on Wi-Fi Fine Time Measurement (FTM) round-trip time (RTT) observations is essential for practical Internet of things (IoT) localization systems. This study investigates a machine learning–based error-correction framework for improving FTM ranging accuracy using low-cost ESP32-S2 devices. A public ESP32-S2 FTM dataset was employed in terms of indoor, outdoor and semianechoic environments, and four regression models were assessed: gradient boosting, random forest, decision tree, and XGBoost. The correction term was the models trained on the difference between the ground-truth distance and the distance value estimated from the physics-based RTT model. Using the full pipeline, including feature engineering and isotonic calibration, the best overall configuration reduced the mean absolute error (MAE) from 3.41 m for the physics baseline to 0.97 m. Environment-specific analysis showed that random forest achieved submeter MAE in outdoor scenarios (0.071 m at 20 m and 0.175 m at 40 m), while indoor MAE was approximately 0.56–0.61 m across models. Performance in the semianechoic environment remained substantially weaker, with MAE above 1.4 m and <i>R</i>² (coefficient of determination) roughly 0.32. The main contribution lies in an integrated seven-stage ranging pipeline that combines physics-based initialization, error-target learning, engineered features, model tuning, output calibration, and environment-specific interpretation. The results show that postprocessing the measurement using software can significantly enhance the accuracy of FTM ranging on the ESP32-S2, while leaving the measurement hardware unchanged.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148615723","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 Energy-Aware Dual-Intelligence Protocol for Dynamic and Self-Optimizing Underwater Wireless Sensor Networks","authors":"Anoop Sreeraj,&nbsp;P. Vijayalakshmi,&nbsp;V. Rajendran","doi":"10.1002/dac.70558","DOIUrl":"https://doi.org/10.1002/dac.70558","url":null,"abstract":"<div>\u0000 \u0000 <p>Underwater wireless sensor networks (UWSN) have been proven essential in providing solutions for various purposes ranging from aquatic surveillance to marine exploration and defense. However, such networks suffer from the drawback of being hindered by several aspects including lengthy propagation delay times, scarcity of energy supplies, changing network structures, and unstable acoustic mediums—issues that heuristic and static methods cannot resolve. Driven by these challenges, the Optimized Clustering and Energy-Aware Network Protocol called OCEANet has been proposed in this research. This protocol is based on a double intelligence approach for a self-adapting dynamic underwater network environment. Its unique feature lies in combining the evolutionary biology-based clustering technique with software-defined radio configuration through artificial intelligence techniques. The OCEANet system comprises two operational phases that complement each other. The clustering and evolutionary bio-beaconswarm routing algorithm selects the appropriate cluster heads considering their residual energy, location, and link quality and thus helps create the optimal multi-hop route toward the sink node. The Self-Updating Reconfigurable Framework uses the Deep Q-Network reinforcement learning technique along with Graph Convolutional Network–based transfer learning. The proposed OCEANet outperforms the other models with a packet delivery ratio of 94% and throughput of 189.18 kbps when there are 100 nodes. Also, while lowering the energy usage and delays, and by increasing the network life cycle, OCEANet establishes it as a reliable, scalable solution for next-generation underwater sensor networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534018","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 Two-Stage Resource Allocation Algorithm for Priority-Aware QoS Optimization in LTE Networks","authors":"Samar Sindian,&nbsp;Eman Chehade,&nbsp;Hadeel Sleem","doi":"10.1002/dac.70572","DOIUrl":"https://doi.org/10.1002/dac.70572","url":null,"abstract":"<div>\u0000 \u0000 <p>As mobile cellular communication technology advances and wireless mobile devices become increasingly popular, multimedia applications have become essential in modern society. Long-term evolution (LTE), launched in 2009, has established itself as a leading cellular technology by providing high-speed data and media transport. Its successor, LTE-Advanced (LTE-A), further enhances this capability with greater bandwidth and peak data rates, enabling effective multimedia transmission beyond traditional voice communication. To ensure consumer satisfaction, high quality of service (QoS) is critical. This paper presents an innovative resource allocation scheme tailored for various services in the downlink of LTE systems, emphasizing service differentiation as a vital factor for QoS, particularly for real-time traffic. We provide a comprehensive overview of LTE architecture, its components, and their interconnections, followed by an in-depth discussion of resource allocation, scheduling techniques, and QoS mechanisms in LTE. Furthermore, we review existing studies and algorithms, leading to the introduction of our proposed Two-stage resource allocation with user satisfaction (TSRAUS) algorithm. Key findings demonstrate that the TSRAUS algorithm significantly improves resource utilization and user experience by effectively managing priorities between real-time and nonpriority applications. Comprehensive statistical analysis, including confidence intervals and significance tests, rigorously validates the TSRAUS algorithm's superior performance across key QoS metrics. The conclusion summarizes these findings and highlights potential future enhancements, including the extension of the algorithm to multicell scenarios, user mobility considerations, and adaptive mechanisms to better address evolving network demands.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534016","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":"Congestion Control in 5G/6G Networks: An Efficient Multi-Relational Skeleton Graph Attention Networks With Greater Cane Rat Optimization Algorithm","authors":"R. Mohanapriya,&nbsp;M. A. Gunavathie,&nbsp;S. Jacophine Susmi,&nbsp;A. Padmavathi","doi":"10.1002/dac.70559","DOIUrl":"https://doi.org/10.1002/dac.70559","url":null,"abstract":"<div>\u0000 \u0000 <p>The emergence of 5G and the imminent deployment of 6G networks have revolutionized wireless communication by enabling ultra-reliable low-latency communication, enhanced mobile broadband, and massive machine-type communication. While these diverse applications foster increasingly complex congestion scenarios due to highly dynamic traffic patterns, diverse requirements of different services, and ultra-dense deployments of the network, efficient congestion control has become a pressing challenge. Conventional methods cannot address the nonlinear and multi-relational characteristics of data traffic. Therefore, with the rapid scaling of connected devices with heterogeneous service demands, bottlenecks will be experienced, which leads to packet loss, increased latency, and poor QoS. Given the above challenges, this paper introduces an advanced congestion control framework developed on top of intelligent graph-based learning and optimization strategies. The input data is from the DeepSense 6G dataset and preprocessed using <i>Z</i>-score and min–max normalization to enhance the stability and uniformity of the preprocessed data. The feature selection is further fine-tuned through the Orchard Algorithm (OA), ensuring highly relevant feature selection. An innovative combination of Multi-Relational Skeleton Graph Attention Networks is proposed to cater to the challenge of understanding multiple relational behaviors in data traffic. Furthermore, the performance of the integrated model is optimized with the Greater Cane Rat Optimization Algorithm to enhance learning efficiency and the precision of congestion control. Experimental analysis demonstrates an outstanding accuracy of 99.9%, ensuring the proposed approach effectively mitigates congestion in 5G/6G networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148534017","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":"CatBoost-SMO-Based Congestion Prediction and Avoidance Using Rap Protocol in Active Distribution Networks","authors":"S. K. Uma Maheswaran,&nbsp;Nidhi Ranjan,&nbsp;David Neels Ponkumar Devadhas,&nbsp;B. Annapurna","doi":"10.1002/dac.70542","DOIUrl":"https://doi.org/10.1002/dac.70542","url":null,"abstract":"<div>\u0000 \u0000 <p>Internet of Things (IoT) devices communicate with the internet to exchange data, requiring an efficient network. IoT monitors events via sensor nodes, sending the collected data to an IoT gateway. The network's rapid growth has led to congestion, causing delays, packet loss, reduced throughput, and poor energy efficiency. Predicting congestion is crucial for minimizing data loss. IoT networks generate heterogeneous, nonlinear data due to the variety of devices and complex interactions. Nonlinear datasets provide challenges for traditional machine learning algorithms, and overfitting can lead to misclassification of real network traffic. To address these constraints, a machine learning and protocol-based approach is used to predict congestion and congestion avoidance in active distribution networks. Initially, input is collected from the congestion detection evaluation dataset and preprocessed using the missing completely at random (MCAR) method to replace missing values. Ordered quantile normalization (ORQN) is used to standardize values in the input dataset. Next, the dataset's dimensionality gets reduced using uniform manifold approximation and projection (UMAP). After that, starling murmuration optimization (SMO)–based categorical boosting (CatBoost) is used for congestion prediction. Lastly, the rate aware protocol (RAP) is applied to mitigate congestion within the IoT network. A simulation study shows that the proposed technique attains 97.44% accuracy, 97.12% recall, and 97.74% precision. Analytical simulations show that the RAP protocol achieves better performance, lower energy consumption, longer network lifetime, higher throughput, and lower delay than existing protocols. Thus, this proposed approach is the best choice for congestion prediction and data transmission for avoiding congestion in active distribution networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533807","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":"Securing Cloud-Based Wireless Sensor Networks Against Botnet Attacks Using Multi-Relational Cascaded Graph Convolutional Neural Network With Puma Optimizer","authors":"D. Karunkuzhali,&nbsp;Krishna Prakash Arunachalam,&nbsp;Abhishek Sharma,&nbsp;RakeshKrishnarao Kadu","doi":"10.1002/dac.70552","DOIUrl":"https://doi.org/10.1002/dac.70552","url":null,"abstract":"<div>\u0000 \u0000 <p>The fundamental challenge is the precise identification of advanced attack patterns in a massive-scale, heterogeneous traffic, maintaining data integrity and traceability. Inspired by these constraints, this work proposes a new Blockchain-based Multi-relational Cascaded Graph Convolutional Neural Network with Puma Optimizer (M-CGCNNet-PO). The process starts with three benchmark datasets: data collection N-BaIoT, TON_IoT, and Bot-IoT, followed by pre-processing with a New Adjusted Min-Max technique coupled with Decimal Scaling and Statistical Column Normalization. Deep semantic features are obtained through a Contrastive Transformer Network (CTNet), and subsequently input to the M-CGCNNet for graph modeling in multiple relations. The Puma Optimizer optimizes the training, and intrusion logs are stored safely through a Blockchain-based Proof of Evolutionary Model (PoEM). Experimental results demonstrate outstanding performance with all datasets, reaching up to 99.68% accuracy, 99.45% F1-score, and high MCC and Kappa values, validating the robustness and reliability of the model. In summary, the suggested M-CGCNNet-PO provides a scalable, precise, and secure model for botnet detection in cloud-based WSNs.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533806","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":"Dual-Port Ceramic Array Antenna Integrated With Polarization Converter for 5G mm-Wave Networks","authors":"Ashutosh Gupta,&nbsp;Ankit Pandit,&nbsp;Sanjeev Kumar Gupta,&nbsp;Laxmi Singh","doi":"10.1002/dac.70570","DOIUrl":"https://doi.org/10.1002/dac.70570","url":null,"abstract":"<div>\u0000 \u0000 <p>A two-port dielectric antenna for mm-wave frequency range has been constructed and examined in this study. The alumina ceramic resonator is excited by the structure via aperture coupling. The design's originality is emphasized by three salient features: (a) Circularly polarized waves may be produced in the working range of 31.8–32.45 GHz using polarization convertor suspension; (b) 1 × 2 array formation improves measured gain close to 9.5 dBi; and (c) antiparallel placement of antenna terminals/SNG MS suspension reduces the coupling level to below −35 dB. An effective working range of 31.45–33.25 GHz is confirmed by experimental validation. Broadsided radiation is guaranteed by the excitation of the basic hybrid HEM_11δ mode. Due to stable radiation feature and diversity parameters, the suggested antenna is applicable for the lower portion of the mm-wave spectrum and future FR2 extensions.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533808","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":"Design of Compact Self-Diplexing Antenna With DS-SRR Loaded Ground for Sub-6 GHz Applications","authors":"Praveena Sambathkumar,&nbsp;Krishnamurthy Ramanujam","doi":"10.1002/dac.70568","DOIUrl":"https://doi.org/10.1002/dac.70568","url":null,"abstract":"<div>\u0000 \u0000 <p>A compact self-diplexing meander patch antenna is proposed for sub-6 GHz 5G and WLAN applications. The proposed antenna consists of a 40° tapered S-shaped meander patch, along with a dual–split split-ring resonator (DS-SRR) integrated into the ground plane. In this design, the integrated DS-SRR acts as a non-radiating frequency-selective element, while the meander patch serves as the primary radiating structure. To achieve inherent band separation, two meandered feed lines are strategically placed to excite different modal regions of the radiator. The antenna operates at two different resonant frequencies, 5.8 GHz and 3.5 GHz, providing gain values of 2.63 dBi and 2.3 dBi, respectively. The DS-SRR introduces localized magnetic resonance and impedance tuning at the upper frequency band while maintaining its non-radiating nature and improving port isolation. Simulation results validate effective self-diplexing operation, where each port supports only its designated frequency band with an inter-port isolation better than −20 dB. Owing to its compact size, reduced fabrication cost, and independent high-band tuning capability achieved without the use of SIW walls or via-based cavities, the proposed antenna is well suited for compact sub-6 GHz wireless communication devices.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"39 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2026-07-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148533777","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}