International Journal of Communication Systems最新文献

{"title":"PAPR Reduction Using Discrete Forest Optimization Algorithm Based on SLM Technique in Intensity Modulated Direct Detection Optical OFDM Communication Systems","authors":"Mahmoud Alhalabi,&nbsp;Necmi Taşpınar,&nbsp;Mohammed Wadi","doi":"10.1002/dac.70126","DOIUrl":"https://doi.org/10.1002/dac.70126","url":null,"abstract":"<div>\u0000 \u0000 <p>In intensity-modulated direct detection optical orthogonal frequency division multiplexing (IM/DD-OOFDM) communication systems, a lower peak-to-average power ratio (PAPR) is essential for improving system performance. In order to reduce the high PAPR, a discrete forest optimization algorithm (DFOA) is integrated with the classical selective mapping (SLM) method in IM/DD-OFDM system. This approach successfully optimizes the values of phase factors, minimizes the search numbers, and reduces computational complexity. To evaluate the impact of the DFOA-SLM method on PAPR reduction, the parameters of the DFOA-SLM method play a crucial role in decreasing the PAPR in an IM/DD optical OFDM system. The DFOA-SLM method demonstrates improved bit error rate (BER) performance, power spectral density (PSD), and power saving performance compared with other PAPR reduction methods. Numerical results indicate that the proposed PAPR reduction method outperforms existing other methods for optical OFDM signals. Specifically, by implementing this technique in the IM/DD optical OFDM communication system, we achieved a decrease in PAPR from 10.68 to 4.88 dB at a complementary cumulative distribution function (CCDF) of 10⁻³, resulting in a reduction of 5.8 dB. Additionally, the computational complexity of the DFOA-SLM method shows a 73.63% improvement over the classical SLM method when the search number is set to 512.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144091815","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":"Integrated Clustering and Optimization for IoT Sensor Networks in Space–Air–Ground Frameworks: A Focus on Energy Savings","authors":"Iman Dakhil Idan Saeedi,&nbsp;Ali Kadhum M. Al-Qurabat","doi":"10.1002/dac.70123","DOIUrl":"https://doi.org/10.1002/dac.70123","url":null,"abstract":"<div>\u0000 \u0000 <p>The integration of space–air–ground networks necessitates effective strategies for managing the energy consumption and operational longevity of IoT sensor nodes. Clustering, implemented as the foundational tier in SAGINs, is instrumental in organizing sensor nodes into efficient communication groups, thereby optimizing data aggregation and minimizing redundant transmissions. This study introduces an energy-efficient cluster head (CH) selection using osprey optimization algorithm (EECHOOA), to minimize the total energy expenditure by each sensor at the individual node level. These sensors are controlled by a CH that transmits data to the top levels. With the osprey optimization algorithm (OOA), we further improve the clustering procedure for accurate CH election. By emulating the unique strategies of ospreys, the OOA adaptively determines the best CHs, taking into account both the distance between nodes and their energy reserve. In comparison to cutting-edge techniques like MMABC, NCOGA, PUAG, and ZFO-SHO, the simulation findings show that our suggested clustering strategy combined with OOA to CH election made the network lifetime is extended by 50%–100% and the network consumption of energy is reduced by 56.25%–76.35% than existing protocols. In order to provide more sustainable and streamlined IoT-based networks capable of responding to a range of fields of application, this study shows how clustering techniques may be used in combination with expert optimization algorithms in SAGINs.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074379","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":"Analysis of Dual Hop RF-UWOC System With RF Energy Harvesting for Marine Applications","authors":"Shaik Mohammed Ali,&nbsp;Hemanta Kumar Sahu,&nbsp;Sudhansu Sekhar Singh","doi":"10.1002/dac.70128","DOIUrl":"https://doi.org/10.1002/dac.70128","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper presents a comprehensive performance analysis of a dual-hop radio frequency-underwater wireless optical communication (RF-UWOC) system incorporating simultaneous wireless information and power transfer (SWIPT) for marine applications. The proposed system features an energy-harvesting relay, modelled as a buoy access point (BAP), that forwards data from multiple ground stations (GSs) to an underwater destination via hybrid RF and UWOC links. We employ a Markov chain-based user selection strategy at the transmitter to address the stochastic nature of GS availability and traffic load. The RF and UWOC links are modelled using Nakagami-<span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mi>m</mi>\u0000 </mrow>\u0000 <annotation>$$ m $$</annotation>\u0000 </semantics></math> fading and an exponential-generalized gamma (EGG) distribution, respectively, capturing realistic fading and turbulence conditions. Closed-form expressions for the average bit error probability (ABEP) are derived for both amplify-and-forward (AF) and decode-and-forward (DF) relaying schemes, incorporating nonlinear energy-harvesting constraints. Analytical results are validated through simulations and asymptotic analysis, revealing the influence of modulation schemes, power splitting ratios, turbulence conditions, and traffic intensity on system performance. The findings provide new design insights for robust, self-sustaining underwater communication networks in energy-constrained marine environments.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074629","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 Distributed Fuzzy Trust-Aware Multipath Routing Protocol in Wireless Sensor Networks","authors":"Hossein Jadidoleslamy","doi":"10.1002/dac.70118","DOIUrl":"https://doi.org/10.1002/dac.70118","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks (WSNs) typically comprise numerous sensor nodes alongside one or more sink. Various challenges, like node misbehavior, improper selection of peer nodes, severe resource constraints, and unbalanced energy utilization throughout the routing process of data packets, as well as inadequate fault tolerance and reliability, low throughput, potential security threats, and insecure operational environments, degrade the overall performance of WSNs. A significant solution for these issues is the implementation of secure routing mechanisms. Consequently, this paper focuses on trust management systems (TMSs) and multipath routing protocols; it proposes a distributed fuzzy trust-aware multipath routing protocol specifically designed for homogeneous WSNs. This novel approach aims to integrate the trustworthiness of nodes within the multipath routing process. Finally, the performance of the proposed protocol has been meticulously analyzed, evaluated, and compared with other existing approaches including Shahbaz et al., IEEMARP, TARF, and SEEM routing protocols, considering a variety of parameters. For the performance analysis of them, the TRMSim-WSN and NS-2 simulation platforms have been selected for simulation, while Expert Choice and grey relational analysis tools have been utilized for statistical analysis. The conducted simulation experiments and statistical analysis indicate that the protocol presented in this study yields better performance; it significantly enhances the balanced and distributed consumption of network resources, scalability, throughput, fault tolerance, accuracy, average of packet loss rate, and provides more reliable paths than other protocols. However, its performance is degraded by factors such as memory consumption, computational complexities, routing overhead, and transmission delays when compared with other algorithms.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144074630","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 Variable Delay Supported Path Loss Model for Underwater Acoustic Sensor Network","authors":"M. Saranya Nair,&nbsp;R. Ratheesh","doi":"10.1002/dac.70119","DOIUrl":"https://doi.org/10.1002/dac.70119","url":null,"abstract":"<div>\u0000 \u0000 <p>In underwater acoustic sensor networks (UASNs), the most complicated issues are higher latency, propagation delay, and transmission loss. This work presents an enhanced path loss model for the UASN to minimize these issues. Initially, random locations of sensor nodes are generated in the UASN environment. Then, the unknown depth of each sensor node is calculated. The unknown depth is computed by the distance between the source and each node. Subsequently, the status of each node is computed. Afterwards, an accurate channel is modeled by considering various parameters like spreading loss, absorption loss, sound propagation, and transmission path loss. This accurate channel model reduces the delay of communication. Then, the transmission loss is computed for the acoustic links to find the link connectivity. In case of loss in connectivity, new node positions are selected using the weighted moving average-based adaptive horse herd optimization with optimal beacon based on the mobility of nodes. Finally, the network reliability is evaluated for the developed path loss model. The performance of the proposed approach is compared with different existing approaches in terms of various performance metrics such as transmission loss, attenuation coefficient, probability density function (PDF), throughput, and average delay. The performance results proved that the proposed approach outperforms the other existing approaches.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143949762","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":"Enhanced Arithmetic Optimization Algorithm for Intrusion Detection in Wireless Sensor Networks","authors":"Mohammed Otair,&nbsp;Faten Ali Qawaqzeh,&nbsp;Saleh Ali Alomari,&nbsp;Raed Abu Zitar,&nbsp;Hazem Migdady,&nbsp;Kashif Saleem,&nbsp;Aseel Smerat,&nbsp;Anas Ratib Alsoud,&nbsp;Laith Abualigah","doi":"10.1002/dac.70122","DOIUrl":"https://doi.org/10.1002/dac.70122","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks (WSNs) face significant security challenges because of their resource constraints and exposure to malicious attacks. Traditional intrusion detection systems (IDSs) often suffer from low detection accuracy, high false alarm rates, and long processing times. To address these issues, this paper proposes an enhanced IDS framework based on the arithmetic optimization algorithm (AOA) for feature selection, combined with support vector machine (SVM) for classification. A new cost function is introduced to guide the feature selection process and improve model performance. The approach, named AS_IDS, is evaluated on the NSL-KDD dataset, achieving an accuracy of 96.65%, a detection rate of 98.69%, and a false alarm rate of 0.04% using only 15 features, with a significant reduction in execution time. Comparative results with state-of-the-art methods demonstrate the effectiveness and efficiency of the proposed framework in enhancing intrusion detection in WSNs.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143944577","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":"Golden Jackal and Enhanced Remora Optimization-Based Sink Mobility for Energy Hole Mitigation in Underwater Wireless Sensor Network","authors":"Keshav Kumar Tiwari,&nbsp;Samayveer Singh","doi":"10.1002/dac.70114","DOIUrl":"https://doi.org/10.1002/dac.70114","url":null,"abstract":"<div>\u0000 \u0000 <p>Underwater wireless sensor networks (UWSNs) face challenges like limited bandwidth, high-energy consumption, and the energy hole problem, where nodes near sinks deplete energy faster, reducing network performance and lifespan. To address these issues, we propose hybrid optimization-based sink mobility for energy hole mitigation in UWSNs (HOSEMU), utilizing a hybrid golden jackal optimization (GJO) and enhanced remora optimization (ERO) approach, termed GJERO. GJERO combines GJO's global search and ERO's local optimization to enhance cluster head (CH) selection, balancing energy consumption and improving convergence. Sink mobility toward energy-depleted CHs further ensures efficient data collection and extended network lifespan. Simulation results in MATLAB show that HOSEMU outperforms existing methods, improving stability by 19.4% over energy-efficient routing and stable data reporting algorithm (EERSDRA) and by 28.7% over energy-conserving enhanced remora optimization (ECERO). These results demonstrate HOSEMU's effectiveness in addressing UWSN-specific challenges and enhancing performance.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 10","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939203","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":"3M-Net: Automatic Modulation Recognition Based on Multiscale Mobile Inverted Bottleneck Convolution and Manhattan Self-Attention Network","authors":"Dan Jing,&nbsp;HuiLu Mo,&nbsp;Liang Han,&nbsp;HongFei Yin,&nbsp;Liangchao Li,&nbsp;Yan Zhang,&nbsp;Ming Li,&nbsp;Mian Pan,&nbsp;Liang Guo","doi":"10.1002/dac.70109","DOIUrl":"https://doi.org/10.1002/dac.70109","url":null,"abstract":"<div>\u0000 \u0000 <p>The increasingly complex modern communication environment poses challenges for automatic modulation recognition (AMR) techniques. In AMR tasks, in order to more comprehensively capture signal features and improve recognition performance, we propose a model named Multiscale Mobile Inverted Bottleneck Convolution and Manhattan Self-Attention Network (3M-Net). In this 3M-Net, the MSMB block is designed to extract multiscale local features of the signals, and the MMG block is designed to enhance global information modeling of the model. Then, a hierarchical backbone that contains the two blocks is designed to extract multilevel features. Extensive experiments on the RML2016.10a and RML2018.01a datasets demonstrate that the 3M-Net model achieves superior recognition performance.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 9","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143939204","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 Comprehensive Review of Wideband Rectennas and Design Challenges","authors":"Parul Saini,&nbsp;Shivani Malhotra,&nbsp;Lipika Gupta","doi":"10.1002/dac.70117","DOIUrl":"https://doi.org/10.1002/dac.70117","url":null,"abstract":"<div>\u0000 \u0000 <p>Radio frequency energy harvesting (RFEH) presents a sustainable and maintenance-free solution for powering wireless sensor networks and Internet of Things (IoT) devices by converting ambient RF signals into usable electrical power. The previously leading single-band RFEH technology was limited to one frequency only, posing a risk of unproductive operation when that frequency is unavailable. This paper examines and explores the different strategy of wideband RFEH system and provides an overview of the latest advancements in wideband rectennas. The paper incorporates a comprehensive categorization of wideband rectennas that outlines the antenna type, rectifier topology, diode type, impedance matching network, and power conversion efficiency employed in each wideband rectenna design. The incorporation of a detailed table including various parametric study enriches the review with empirical data, thereby enhancing its practical significance. The discussion of design challenges, rectifier topologies, and methods to boost power conversion efficiency addresses crucial technical aspects of wideband rectifiers, filling gaps in current research literature. By combining a thorough examination of design challenges and various methodologies, the paper proves to be a valuable asset for enhancing the effectiveness and adaptability of wideband rectifiers in RFEH applications.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 9","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143930289","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 Threat Flow Classification Method Based on Feature Fusion and Weighted Attention","authors":"Yanli Tu,&nbsp;Yu Wu,&nbsp;Shizheng Feng,&nbsp;Jiaxin Ren,&nbsp;Han Shen,&nbsp;Yuzhen Zhang,&nbsp;Qianwen Liu","doi":"10.1002/dac.70092","DOIUrl":"https://doi.org/10.1002/dac.70092","url":null,"abstract":"<div>\u0000 \u0000 <p>With the rapid development of the Internet, the increasing network traffic has brought a greater burden to network management. At the same time, abnormal traffic attacks on network equipment pose significant security risks. Classifying network traffic on network devices is an important way to protect information security. However, due to the vast amount and high-dimensional attributes of traffic data, existing traffic classification models are mostly complex in structure, with a large number of parameters, making them difficult to apply to network devices with limited computing resources. Hence, this paper proposes a threat flow classification method based on feature fusion and weighted attention (FFWCA) to save storage and computing costs while ensuring model accuracy. Firstly, it constructs a lightweight multiscale feature extraction module by dilated convolutions and <span></span><math>\u0000 <semantics>\u0000 <mrow>\u0000 <mn>1</mn>\u0000 <mo>×</mo>\u0000 <mn>1</mn>\u0000 </mrow>\u0000 <annotation>$$ 1times 1 $$</annotation>\u0000 </semantics></math> convolutions to fuse features of different receptive field sizes. Then, it constructs an inverted residual structure embedded with a weighted coordinate attention mechanism, to extract accurate features for traffic classification and mitigate the gradient vanishing phenomenon brought by the lightweight model, a chapter. Finally, it constructs a fully convolutional structure classifier to reduce the computational overhead brought by the fully connected layer classifier while ensuring the model's nonlinear complexity. FFWCA significantly reduces the model's computational overhead and the number of parameters by incorporating a lightweight multiscale feature extraction module and a weighted coordinate attention mechanism, so that it can be efficiently deployed on network devices with constrain computing resources. Experiments on two public network traffic datasets, Bot-IoT and USTC-TFC2016, demonstrate that FFWCA achieves a balance between performance and lightweight and is suitable for edge computing and IoT devices.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 9","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143919639","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}