International Journal of Communication Systems最新文献

{"title":"Design and Analysis of Compact Four-Port Fractal-Loaded MIMO Antenna for 5-g Application","authors":"Kamani Sneha,&nbsp;Vipul Agarwal","doi":"10.1002/dac.70206","DOIUrl":"https://doi.org/10.1002/dac.70206","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposed a compact four-port fractal-loaded multiple input multiple output (MIMO) antenna for 5G applications. The proposed antenna is fabricated on an FR4 substrate and operates at dual-frequency bands of 29.8133 and 34.2933 GHz, covering a wide bandwidth from 28 to 36 GHz. The design incorporates fractal loading and slots to enhance the bandwidth, which covers the frequency range from 28 to 36 GHz. The orthogonal placement of MIMO antenna elements minimizes mutual coupling, while the coplanar waveguide (CPW) feed efficiently transmits signals. The proposed fractal geometry allows significant size reduction while maintaining optimal performance at 5G frequencies, making the antenna suitable for compact wireless systems. The fractal geometry significantly improves isolation between the antenna elements, achieving an isolation level of −30 dB. The antenna exhibits peak gains of 6.4 dBi at 29.8133 GHz and 5.37 dBi at 34.2933 GHz, demonstrating its suitability for high-speed, low-latency communication. The design process begins with a single-port antenna, transfers to a nonfractal MIMO configuration, and finally develops into the fractal-loaded MIMO antenna. The results show that the proposed fractal-loaded MIMO antenna offers better bandwidth, isolation, and compactness compared to traditional designs, making it ideal for next-generation 5G wireless communication systems.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144758541","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":"Performance of a Reconfigurable Intelligent Surface-Assisted D2D Communication Network Using NOMA: An Overlay Scenario","authors":"P. Baskar,&nbsp;Abhijit Bhowmick,&nbsp;Yogesh Kumar Choukiker","doi":"10.1002/dac.70202","DOIUrl":"https://doi.org/10.1002/dac.70202","url":null,"abstract":"<div>\u0000 \u0000 <p>A reconfigurable intelligent surface (RIS)-assisted device-to-device (D2D) network is studied in this paper where devices are cognitive radio (CR). D2D devices communicate with each other in overlay mode using cellular user (CU) spectrum and non-orthogonal multiplexing (NOMA) scheme. The RIS is strategically positioned to enhance D2D communication performance and to reduce interference effectively. It is considered that the RIS-associated channels are Rician faded while the direct channels are Rayleigh faded; that is, a mixed channel approach is considered. A comprehensive analytical framework is established to describe the signal model and performance parameters from source to destination with the perfect and imperfect successive interference cancellation (SIC). To find the optimal position of RIS, an algorithm is also developed. It focuses on two key performance indicators: outage and throughput. The closed-form expressions of outage and throughput are developed. A simulation platform is developed, and extensive simulations are carried out to study the performance indicators. It investigates the impact of various network parameters, such as sensing time, an imperfection in SIC, interference threshold, and so forth, on outage and throughput.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740399","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":"Optimized Resource Management Using Binarized Spiking Neural Network With Pyramid Attention and Smart Contract Blockchain for Sustainable Spectrum Allocation in 6G","authors":"S. K. Jameer Basha,&nbsp;Singamaneni Krishnapriya,&nbsp;G. Kirubasri,&nbsp;Gunjan Varshney,&nbsp;C. Rama Mohan,&nbsp;Kuldeep Chouhan,&nbsp;Mohan Rao Thokala,&nbsp;Neelima Koppala","doi":"10.1002/dac.70195","DOIUrl":"https://doi.org/10.1002/dac.70195","url":null,"abstract":"<div>\u0000 \u0000 <p>The rapid expansion of connected devices and the need for high-speed communication make sustainable spectrum allocation and resource management crucial issues in 6G networks. Traditional spectrum management methods often rely on static or centralized techniques, limiting adaptability and efficiency in dynamic network environments. Additionally, these methods struggle to balance energy efficiency, latency, and spectrum utilization. To address limitations, this work proposes a novel Binarized Spiking Neural Network with Pyramid Attention Network (BSNN-PAN)-based spectrum allocation approach that integrates Pyramid Attention Networks (PANs) with binarized spiking neural networks (BSNNs). The approach employs Time-to-First-Spike (TTFS) coding to encode input spectrum data into spike trains, which are processed by binary Integrate-and-Fire (IF) neurons. PAN introduces attention weights to capture multiscale spatial and temporal dependencies, enhancing feature extraction and decision-making. The prairie dog optimization algorithm (PDOA) is applied to optimize hyperparameters such as weight, error, and loss, improving adaptability, efficiency, and resource allocation. The collaboration of the three significantly improves decision-making efficiency and security in dynamic environments, demonstrating the added value of their technological integration. Experimental results demonstrate significant improvements, including 1.8-kJ energy consumption, 412-ms transaction latency, and 15-ms average channel allocation time. These outcomes validate the proposed BSNN-PAN framework as an effective and sustainable solution for next-generation 6G spectrum management.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.8,"publicationDate":"2025-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144740198","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 Signal Coverage in Millimeter-Wave Massive MIMO via Efficient Predefined-Time Adaptive Neural Network–Based Beam Training","authors":"Balasubramani Ramesh,&nbsp;Jampani Chandra Sekhar,&nbsp;Thangam Marimuthu,&nbsp;Abdul Satar Shri Vindhya","doi":"10.1002/dac.70186","DOIUrl":"https://doi.org/10.1002/dac.70186","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes an advanced deep learning framework for efficient beam training in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. To overcome the limitations of conventional beam training approaches such as high overhead, slow adaptation to dynamic environments, and poor scalability, an Improving Signal Coverage in Millimeter Wave Massive MIMO via Efficient Predefined Time Adaptive Neural Network based Beam Training (ISC-MMIMO-EPTANN-BT) model is proposed. The proposed model used deep neural network (DNN) to learn complicated nonlinearities in channel power leakage (CPL) and used an efficient predefined time adaptive neural network (EPTANN) to provide real-time responsiveness and temporal synchronism in beam training. The parameters of the model are also optimized using fire hawk optimization algorithm (FHOA) to get better convergence speed and signal coverage. The proposed technique is executed in MATLAB. The proposed approach attains better performance under successful rate by significantly less beam training overhead and also increases signal coverage based on simulation results. The proposed ISC-MMIMO-EPTANN-BT method attains 26.15%, 21.08%, and 33.75% higher successful rates and 16.32%, 28.94%, and 20.24% lower normalized mean square error compared with existing methods such as deep learning for beam training in millimeter wave massive MIMO schemes (BT-MMIMO-DNN), deep learning for combined feedback and channel prediction in large-scale MIMO systems (CNN-JCS-MMIMO), and triple-refined hybrid-field beam training in mmWave extremely large-scale MIMO (TR-FBT-MIMO), respectively. The ISC-MMIMO-EPTANN-BT technique reduced beam training overhead, enhanced signal coverage, and identified a promising candidate for successful beam training in mmWave massive MIMO schemes.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144716942","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":"Compact Two-Port Dual- and Triple-Band MIMO Antennas With Orthogonally Placed Microstrip Monopole Elements for 5G N77/78/79 Sub-6-GHz Applications","authors":"Naguboina Gopi Chand,&nbsp;K. Anusudha","doi":"10.1002/dac.70183","DOIUrl":"https://doi.org/10.1002/dac.70183","url":null,"abstract":"<div>\u0000 \u0000 <p>In today's wireless communication landscape, the demand for compact MIMO antennas with low mutual coupling is critical. To meet this requirement, this paper presents two compact MIMO antenna configurations based on microstrip line principles. Initially, a compact dual-band antenna is designed for 5G N77/N78/N79 sub-6-GHz applications. The introduction of an inverted L-shaped slot into the broadband radiating element enables the generation of two distinct resonances. Without the slot, the antenna covers a broad frequency range from 4.30 to 5.54 GHz. Upon slot insertion, it achieves dual-band operation across 3.3–3.78 GHz and 4.3–5.15 GHz. Subsequently, by integrating an additional inverted L-shaped slot on the opposite lateral side, a triple-band response is realized, covering 3.6–3.85 GHz, 4.75–5.05 GHz, and 5.3–7.5 GHz. Both antenna designs are fabricated on an FR-4 substrate (εᵣ = 4.4, tanδ = 0.025) with 1.6 mm thickness and a compact footprint of 23.3 × 29.125 mm² (0.37λ₀ × 0.46λ₀). The radiating structure possesses an inverted T-shaped geometry occupying (8 × 9.65) + (29.125 × 13.65) mm² that meets the requirements for modern space-limited devices. Furthermore, two compact two-port MIMO configurations (23.3 × 66.06 mm², or 0.37λ₀ × 1.04λ₀) are proposed, utilizing orthogonally placed dual-band and triple-band monopole elements. Electromagnetic simulation using Ansys HFSS confirms that the designs achieve excellent MIMO performance, including envelope correlation coefficients (ECC) below 0.0019 and 0.001, channel capacity loss (CCL) under 0.26 and 0.46 bits/s/Hz, peak gains of 4.9 and 5.1 dBi, and radiation efficiencies exceeding 94% and 85%, respectively, for MIMO antennas with dual-band and triple-band monopole antenna elements. Notably, mutual coupling remains below −23 dB and −24.5 dB across the operating bands, despite maintaining an edge-to-edge spacing of less than 0.125λ.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144705486","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":"Outdoor 2D Localization of Sensor Nodes in Wireless Sensor Networks Using the Lotus Effect Optimization Algorithm","authors":"Goldendeep Kaur,&nbsp;Kiran Jyoti","doi":"10.1002/dac.70175","DOIUrl":"https://doi.org/10.1002/dac.70175","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks (WSNs) impart marvelous connectivity as well as data-gathering facilities. Location detection is a crucial feature of sensor network applications despite being a difficult challenge. When it comes to Internet of Things (IoT) location-based applications like remote healthcare, where prompt emergency or maintenance services are required, precise localization of sensor nodes is needed. The use of Global Positioning Systems (GPS) for outdoor large-scale localizations poses several restrictions because of the high cost of GPS. So in this work, a novel concept of a single static anchor node is utilized for localizing all the movable target nodes. This experimentation has been carried out in real real-time outdoor environment utilizing LoRa Modules to communicate to the LoRaWAN wireless network. These LoRa modules use received signal strength indicator (RSSI) values, and using it, the distance is assessed between a dedicated anchor node and multiple target nodes. The different dataset values of RSSI are utilized to assess the positions of target nodes in real-time environment. The results are then optimized using the lotus effect optimization algorithm (LEA) for localizing the sensors with more precision. The simulation results demonstrate that LEA has the lowest localization error of 0.1645 m and strong optimization capability in contrast to the several strategies employed in 2D environments.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688159","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 Taylor Flamingo Shark Optimization–Based Traffic Aware Content Caching Vehicular Social Networks","authors":"Vedha Vinodha D.,&nbsp;Malathy Subramanium","doi":"10.1002/dac.70188","DOIUrl":"https://doi.org/10.1002/dac.70188","url":null,"abstract":"<div>\u0000 \u0000 <p>Vehicular Social Networking (VSN) is an emerging and developing application of the Internet of Vehicles (IoV) that aims to integrate vehicular networks with social networks seamlessly. Nevertheless, unique vehicular network features, namely, high mobility as well as frequent communication interruptions, make content delivery to end users under strict delay constraints very problematic. The Taylor Flamingo Shark Optimization (TFSO) method is introduced to address the limitations of existing caching and routing strategies in VSN under real-time traffic conditions. With the amalgamation of FSA and WSO with the Taylor series, TFSO provides a powerful tool for accurate, delay-aware, and mobility-sensitive content caching, thereby improving content delivery efficiency in VSNs. The proposed optimization-based traffic-aware content caching is implemented using several stages. Initially, the shortest path with the vehicular content provider is found based on the proposed hybrid Flamingo Shark Optimization (FSO). The FSO is devised by using the Flamingo Search Algorithm (FSA) as well as White Shark Optimization (WSO). Subsequently, traffic-aware content recommendations are carried out based on conditional likelihood probability. Additionally, the vehicular distribution managed by the content provider is optimized across the network by using the proposed TFSO, which is devised using the proposed FSO along with the Taylor series concept. Moreover, the effectiveness of the developed TFSO approach is assessed by leveraging metrics including computational cost, delivery delay, and delivery rate. The computational cost recorded value is 1.057, which shows that the algorithm operates with low computational overhead; the delivery delay of TFSO is 0.611 s, which indicates that the system required less time to deliver content to end users in high-mobility scenarios; and the delivery rate is 85.996, which reflects the high success rate of content delivery across the network using 2000 rounds with 150 vehicles.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687901","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 and Analysis of Sunshine-Shaped MIMO Antenna for High Demand in Data Rates and Ultra-Fast Sixth-Generation Wireless Communications Through THz Spectrum Range","authors":"K. V. Vineetha,&nbsp;M. Siva Kumar,&nbsp;P. Durgaprasadarao,&nbsp;Satti Sudha Mohan Reddy,&nbsp;Kokku Aruna Kumari,&nbsp;Lokesh Raju Vysyaaraju,&nbsp;B. T. P. Madhav,&nbsp;Sk Hasane Ahammad,&nbsp;Mahmoud M. A. Eid,&nbsp;Ahmed Nabih Zaki Rashed","doi":"10.1002/dac.70196","DOIUrl":"https://doi.org/10.1002/dac.70196","url":null,"abstract":"<div>\u0000 \u0000 <p>THz antennas, which function at high speeds, frequencies, and data rates, were developed in response to the increased need for high-speed communication equipment. High data transfer is necessary for wireless communication in modern technologies. After 5G, the next generation of wireless technology is called 6G (sixth-generation wireless). Because 6G networks may run at greater frequencies than 5G networks, their capacity and latency will be significantly increased. Allowing communications with a latency of 1 μs is one of the objectives of the 6G internet. This paper introduces a compact and highly efficient sunshine-slotted MIMO antenna designed for 6G and wireless applications. The antenna features a sun-shaped patch and a partial ground layer to improve its overall performance. The proposed antenna operates across 3.6, 4.5, 5.2, and 6.2 THz, respectively, which are used for wireless communication systems. This work presents a MIMO antenna constructed with a low reflection coefficient value of −34, −38, −18, and −23 dB, with an insertion loss of less than −30 dB over the operational frequency. In addition to this, the antenna has a gain value of 8.5–9.2 dBi. The proposed MIMO antenna also has a minimum ECC value of &lt; 0.01; similarly, across the operating frequency, the antenna has a DG value range of 10–11 dB respectively. The proposed antenna has dimensions of 33 × 33 × 100 μm³ using graphene as a conducting layer and silicon as a substrate layer. The suggested antenna can be utilized for high-speed communications because of its high gain and operating frequency applicability.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144687902","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 Quantum-Crossover Gravitational Search Algorithm for Energy-Efficient Power Allocation in Serial Relaying Underwater Wireless Optical Communication Systems","authors":"Lilly Raamesh,&nbsp;S. Anitha,&nbsp;S. Radhika,&nbsp;A. Chandrasekar","doi":"10.1002/dac.70169","DOIUrl":"https://doi.org/10.1002/dac.70169","url":null,"abstract":"<div>\u0000 \u0000 <p>Underwater wireless optical communication systems face several challenges, such as path loss, poor signal quality, and limited communication range because of environmental constraints like scattering, turbidity, and attenuation. To address these challenges, this study proposes a serial relaying underwater wireless optical communication system enhanced by a hybrid optimization algorithm called quantum-based crossover gravitational search algorithm. This algorithm incorporates a gravitational search algorithm with a quantum crossover mechanism to optimize power allocation among relay nodes for increasing energy efficiency and reducing signal-to-noise ratio under various environmental constraints. This study adopts a gravitational search algorithm for resolving the power allocation problem that utilizes the concept of gravitational attraction among agents to explore the search space. However, it often suffers from slow convergence and local optima trapping. To resolve this, the proposed technique deploys a quantum crossover mechanism to refine this process by improving solution diversity and convergence speed. By combining the significance of these approaches, the proposed quantum-based crossover gravitational search algorithm effectively solves complex optimization issues and enhances energy efficiency by distributing power optimally and reducing excessive energy consumption. Simulation results demonstrate that Q-CROSS GSA outperforms existing optimization methods in terms of energy efficiency, signal-to-noise ratio, and outage probability, offering a robust approach for an efficient UWOC system in challenging underwater environments.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688157","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 Parasitic Microstrip Antenna Design for IoT and 5G Networks Using Attention-Enhanced Graph Convolutional Model","authors":"Veeramani Rajumani,&nbsp;Periasamy Pappampalayam Sanmugam,&nbsp;Anitha Periasmay","doi":"10.1002/dac.70192","DOIUrl":"https://doi.org/10.1002/dac.70192","url":null,"abstract":"<div>\u0000 \u0000 <p>The growing demand for high-speed, reliable wireless communication has accelerated advancements in antenna technology for 5G and IoT applications. However, existing antenna designs often face challenges such as limited bandwidth, inadequate gain, and poor impedance matching, which hinder their ability to meet the stringent performance requirements of modern networks. To address these limitations, this research presents a high-gain, wideband parasitic microstrip antenna designed for 5G and IoT applications, operating at 26 GHz within the 5G new radio Frequency Range 2 (FR2) band n258. The proposed antenna incorporates a miniaturized parasitic patch design featuring eight microstrip patches arranged around a centrally probe-fed active patch in a squared configuration. These parasitic patches are electromagnetically coupled via the magnetic and electric fields generated by the active patch, achieving a compact array with a total dimension of 24 × 24 mm². To enhance antenna performance, a Multi-Layer Attention Graph Convolutional Network (MLAGCN) is utilized to effectively extract key features from the input data, whereas the Gooseneck Barnacle Optimization (GBO) algorithm iteratively fine-tunes the design parameters. The antenna achieves a maximum gain of 12 dB and an efficiency exceeding 95% within the frequency range of 23–28 GHz. This integrated design and optimization approach facilitates cutting-edge performance in terms of bandwidth, gain, and reliability, meeting the rigorous demands of 5G/6G, IoT, and other next-generation services, as well as extending network coverage. This research proposes a compact parasitic microstrip antenna optimized for 5G/IoT using an MLAGCN and GBO. The MLAGCN captures interdependent antenna parameters, whereas GBO fine-tunes design variables for enhanced impedance matching and bandwidth. Results show significant improvement in return loss and wideband performance compared with conventional designs.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 13","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-07-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144688158","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}