International Journal of Communication Systems最新文献

{"title":"Optimizing Secure Data Transmission in Cognitive IoT-WSN: An Energy-Aware Approach With Hybrid POA-SCA and Block Chain Technology","authors":"Gomathi Ramalingam,&nbsp;Palani Uthirapathy","doi":"10.1002/dac.70081","DOIUrl":"https://doi.org/10.1002/dac.70081","url":null,"abstract":"<div>\u0000 \u0000 <p>In the field of cognitive networks, particularly within the Internet of Things and wireless sensor networks, secure and energy-efficient data transmission is crucial. Traditional methods often fall short in optimizing energy and enhancing security during data transmission. Effective key management schemes that are both secure and energy-efficient are still lacking. Moreover, many challenges remain based on high computational overhead, diversity, low throughout, and latency issues, which lead to poor performance. To find the solution for aforementioned issues, this research proposes a novel Multipath Link Routing Protocol for secure and energy-aware data transmission, leveraging optimal cluster head selection within cognitive Internet of Things-wireless sensor networks applications. The sensor data is collected from the environment using sensor nodes. The novel Hybrid Pelican Optimization Algorithm based Sine Cosine Algorithm is suggested to choose optimal clusters during cluster generation. In this, the Sine Cosine Algorithm is integrated into the Pelican Optimization Algorithm to mitigate diversity challenges and ensure proper balancing. Then, the Multipath Link Routing Protocol approach implements numerous paths for dependable and effective data transfer across sensor nodes. Here, pair wise keys are shared by Multipath Link Routing Protocol approach between adjacent nodes to guarantee secure transmission. Additionally, the implementation of homomorphic encryption technique encrypts and decrypts messages to address the key distribution issue for securing transmission during secret key generation. Furthermore, data degradation and retransmission are avoided by this protocol, which uses query, routing request, and route reply to identify the routing from source node to destination node. After that, the creation of a blockchain-assisted authentication framework ensures safe access while guarding against illegal access in cloud-stored data. By encrypting the input data, the hash function applies SHA 512 to generate hash value in blockchain technology. The objective is to create a routing protocol that maximizes the effectiveness of data sharing while taking into account the intrinsic limits of sensor nodes such as computing and energy limitations. By using performance metrics like throughput, latency, and energy efficiency, the system achieves its goals. Compared to prior secure data transmission approaches, the proposed approach attains greater findings of 98.15% throughput, 110-J energy consumption, 87-ms latency, and 98.59% security rate, where the values are greater than other techniques. The simulation findings indicate that the proposed approach successfully improves security and energy efficiency for data transmission in cognitive Internet of Things and wireless sensor networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826922","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":"Trust-Based Multi-Objective Cluster Head Selection for Optimal and Secure Routing in Wireless Networks","authors":"G. C. Jagan,&nbsp;V. Remya,&nbsp;G. Balachandran,&nbsp;S. Ranjith","doi":"10.1002/dac.70095","DOIUrl":"https://doi.org/10.1002/dac.70095","url":null,"abstract":"<div>\u0000 \u0000 <p>Wireless sensor networks, integral to applications such as healthcare, environmental monitoring, and defense, operate under constraints of energy, security, and data reliability, making optimization essential. These networks face challenges such as limited battery life, susceptibility to attacks, and maintaining efficient data transmission in dynamic environments. This research introduces a comprehensive trust-based multi-objective optimization framework for cluster head selection and secure routing, addressing these critical issues. The framework leverages the trusted weight-based hyperbolic sine bobcat optimizer (TWHSBO) for optimal cluster head selection, ensuring energy efficiency, and trust in the network. For secure and efficient data transmission, the Trusted Deep Reinforced-Q Zonal Network (TDRQZN) is employed, combined with the bluefin trevally optimizer (BTO) for optimal path selection. The proposed hybrid framework demonstrates substantial improvements in key performance metrics compared to traditional approaches. Performance metrics such as network lifetime increases by 40%, throughput improves by 30%, and packet loss reduces by 25%, ensuring reliable and secure data transmission. Energy efficiency is achieved through optimized resource allocation, extending the operational lifespan of sensor nodes. The integration of trust mechanisms in the proposed framework mitigates security risks, enhancing data integrity and privacy in sensitive environments.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143826919","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 Levenberg–Marquardt and LSBoosting Ensemble Algorithms for Optimal Signal Attenuation Modeling and Coverage Analysis","authors":"Joseph Isabona,&nbsp;Agbotiname Lucky Imoize,&nbsp;Cheng-Chi Lee","doi":"10.1002/dac.70096","DOIUrl":"https://doi.org/10.1002/dac.70096","url":null,"abstract":"<div>\u0000 \u0000 <p>This paper proposes and engages the Levenberg–Marquardt algorithm method via regression to optimally model and predict real-time signal strength values acquired via telecom software investigation tools in LTE cellular networks. To further improve the Levenberg–Marquardt method, which is sometimes prone to parameter evaporation on high dimensional data with high bias or variance issues during the application, we explore the Least Square Boosting (LSBoosting) ensemble algorithms. The combined signal predictive modeling procedure is termed the hybrid LSBoost-LM method. First, when the proposed hybrid LSBoost-LM method was engaged for real-time extrapolative signal analysis, the results displayed excellent root mean square error precision accuracies compared with two other standards, Bag-LM and LM methods. As a case in point, the LSBoost-LM method achieved 2.15, 3.44, 3.33, 1.31, and 2.19 dB RMSE values at different prediction study locations, which are relatively lower compared with the Bag-LM and standard LM methods that achieved higher RMSE values of 3.38, 3.86, 4.07, 2.28, 3.98 dB and 5.57, 5.52, 5.14, 3.67, 4.56 dB, respectively. Secondly, applying the hybridized model produced up to 93.39% cell area coverage quality and 89.18% fringe cell area coverage quality across the eNodeB study locations. The proposed method can assist practicing RF network planners in realistic cell coverage quality estimation and analysis of related wireless networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818502","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 Broadband Dual-Polarized Magnetoelectric Dipole Antenna With High Isolation","authors":"Wei-Wei Peng,&nbsp;Kai Jie Tang,&nbsp;Duo-Long Wu","doi":"10.1002/dac.70097","DOIUrl":"https://doi.org/10.1002/dac.70097","url":null,"abstract":"<div>\u0000 \u0000 <p>A broadband, low-profile, and dual-polarized magnetoelectric dipole (MED) antenna with high isolation is proposed for in-band full-duplex applications. The proposed MED antenna is configured with a cross-dipole, copper cylinders, instead of the traditional vertical metal walls, and a ground. Two different feeding methods, a T-shaped strip connected with a T-junction power divider for Port 1 and a microstrip-to-slot coupling structure for Port 2, are designed to excite dual-polarized radiation. Compared to the previous works, the height of the MED antenna is from the conventional about 0.25 λ₀ to 0.15 λ₀, where λ₀ is the wavelength in free space at the center operating frequency. The broadband, dual-polarized, and high port-to-port isolation characteristics are reserved. A designed prototype is fabricated, and the measured results demonstrate an overlapped −10-dB impedance bandwidth of 1.73–2.70 GHz (43.8%), the port-to-port isolation of 44.1 dB, the average realized gains of 8.89 and 8.49 dBi, and the average radiation efficiency of 86.1% and 87.1% for Ports 1 and 2, respectively. These characteristics make the proposed antenna a promising candidate for in-band full-duplex base station systems.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818504","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":"Hybris-E2: A Novel Routing Protocol for Energy Efficiency and Load Balancing in MANETs","authors":"R. Vinod Kumar,&nbsp;Dhanalakshmi Gopal,&nbsp;V. S. Nishok,&nbsp;B. Senthilkumaran","doi":"10.1002/dac.70093","DOIUrl":"https://doi.org/10.1002/dac.70093","url":null,"abstract":"<div>\u0000 \u0000 <p>In the rapidly evolving landscape of wireless networks, mobile ad hoc networks (MANETs) have emerged as a crucial technology for enabling communication in dynamic and infrastructure-less environments. Particularly in disaster recovery scenarios, where traditional communication infrastructures may be compromised, MANETs provide a flexible and resilient means of ensuring the continuous flow of information among mobile nodes. However, the efficiency and reliability of MANETs are often hindered by two primary challenges: energy consumption and load balancing. The rapid deployment of MANETs in disaster recovery operations poses significant challenges, particularly in energy efficiency and load balancing. This study presents Hybris-E2, a novel routing protocol designed to address these challenges by integrating a hybrid clustering approach with dynamic power control (DPC) and adaptive traffic shaping (ATS). The protocol's multi-layered architecture optimizes energy consumption by adjusting transmission power according to node distance while simultaneously ensuring balanced traffic distribution across the network. Through extensive simulations under various network scenarios, Hybris-E2 demonstrated superior performance in terms of energy efficiency, network lifetime, packet delivery ratio, and scalability compared to existing protocols. The proposed protocol is executed in the NS3 simulation environment and achieves an accuracy of 95.5% in packet delivery ratio, making it a robust solution for maintaining efficient communication in MANETs, particularly in unpredictable and high-demand environments such as disaster recovery.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143818503","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 Quantum Deep Convolutional Generative Adversarial Networks for Channel Prediction and Performance Enhancement in Large-Scale MIMO-OFDM Systems","authors":"P. Vijayakumari,&nbsp;M. Raja,&nbsp;Shaik Rahamtula,&nbsp;P. Sree Lakshmi,&nbsp;P. Janardhan Saikumar","doi":"10.1002/dac.70086","DOIUrl":"https://doi.org/10.1002/dac.70086","url":null,"abstract":"<div>\u0000 \u0000 <p>Multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) systems demand accurate channel prediction for optimal performance. This research presents an innovative approach employing a hybrid quantum deep convolutional generative adversarial network (HQDCGAN) to enhance channel prediction, minimize error vector magnitude, reduce peak power, and mitigate adjacent channel leakage ratio (HQDCGAN-MIMO-OFDM) proposed. This approach implements a peak-to-average power ratio (PAPR) reduction module utilizing HQDCGAN trained with lower PAPR data acquired through simplified clipping with filtering (SCF) technique. The proposed HQDCGAN architecture leverages pyramidal dilated convolutions and attention mechanisms to extract multi-scale features from OFDM channel data. By incorporating attention mechanisms, the model dynamically focuses on crucial information, refining the channel prediction process. The primary objective is to exploit the network's capability to learn complex spatial–temporal correlations within OFDM channel signals. These strategy goals are to significantly improve the accuracy and, robustness of channel prediction, leading to minimized error vector magnitude (EVM) and mitigated issues related to peak power and adjacent channel leakage ratio (ACLR). To validate the efficiency of the proposed HQDCGAN-MIMO-OFDM the evaluation metrics such as spectral efficiency, peak-to-average power ratio, BER, SNR, and throughput are quantitatively analyzed. The proposed method CP-LSMIMO-OFDM-HQDCGAN gives 20.67%, 12.78%, and 19.56% low bit error rate, 21.66%, 23.09%, and 25.11% low reduction in PAPR and 23.76%, 30.45% and 18.97% high throughput with existing methods like TOP-ADMM, RNN-DNN-MIMO-OFDM, and IA-MIMO-OFDM methods, respectively.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143809391","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":"Hardware Implementation of Fuzzy Logic-Based Energy-Efficient Routing Protocol for Environment Monitoring Application of Wireless Sensor Networks","authors":"Prakash Saxena,&nbsp;Sarita Singh Bhadauria","doi":"10.1002/dac.70087","DOIUrl":"https://doi.org/10.1002/dac.70087","url":null,"abstract":"<div>\u0000 \u0000 <p>The application of wireless sensor network (WSN) technology provides a cost-effective, intelligence-driven solution for addressing various challenges. WSNs have emerged as a highly promising technology, finding applications in environmental monitoring, surveillance, and the development of smart cities. However, a primary challenge in WSNs is the limited energy resources of individual sensor nodes. Preserving energy is crucial to extend the network's operational lifespan and ensuring multihop data transmission. The main objective of this work is to develop a routing protocol focused on enhancing energy efficiency within hybrid WSNs for environmental monitoring and implementing it on a hardware. This protocol integrates methodologies such as data aggregation, cluster-based routing, and sleep scheduling to optimize energy utilization effectively and extend the network's operational longevity. By considering factors like residual energy and proximity to neighboring nodes, this innovative protocol employs sleep scheduling techniques. This allows certain nodes to conserve energy through periodic transitions into low-power sleep modes. The proposed routing protocol undergoes rigorous evaluation through extensive experiments and comparative analysis with existing protocols, specifically in terms of energy consumption and network lifespan. The results conclusively highlight a substantial enhancement of energy efficiency achieved by this protocol, leading to a notably prolonged network lifespan and an overall boost in performance. The insights derived from this protocol's findings contribute significantly to the domain of hybrid WSNs, offering valuable guidance for the design and implementation of energy-efficient routing protocols in real-world scenarios.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 8","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793686","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 AI-Driven Graph-Swarm THz Slice Optimizer for Terahertz Frequency Management and Network Slicing in 6G/7G ORAN Networks","authors":"Akanksha Gupta,&nbsp;Amira Nisar","doi":"10.1002/dac.70077","DOIUrl":"https://doi.org/10.1002/dac.70077","url":null,"abstract":"<div>\u0000 \u0000 <p>As 6G and 7G networks evolve, the efficient management of the Terahertz (THz) frequency band and network slicing in Open Radio Access Network (ORAN) architectures is critical to support ultra-high-speed data transmission, diverse service requirements, and dynamic network conditions. This research addresses key challenges such as interference management in the high-density THz spectrum, unpredictable traffic patterns, and fluctuating service demands in network slicing. The proposed AI-Driven Graph-Swarm THz Slice Optimizer Framework introduces two novel components: Co-Annealed Graph-AE OptiNet for real-time THz frequency optimization and Deep Q-Cat Memory Net for adaptive network slicing. The Co-Annealed Graph-AE OptiNet dynamically models the ORAN network state, predicts interference, and optimizes spectrum allocation, achieving 95.7% spectrum efficiency and 2.2% interference rates, ensuring minimal signal degradation. Simultaneously, the Deep Q-Cat Memory Net learns optimal slicing strategies, predicts congestion, and proactively allocates resources, resulting in 97.8 Gbps throughput, 0.8 ms latency, and improved bandwidth utilization. Simulation results validate the framework's effectiveness, showcasing significant improvements over existing models in all key performance metrics, including low latency, enhanced resource utilization, and robust adaptability. These findings highlight the framework's potential to enable scalable and efficient network management in future-generation wireless networks.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 7","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143793684","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":"Optimizing Blockchain Communication Systems Security With Deep Logic Sparse Autoencoder and Kookaburra Search–Based Intrusion Detection","authors":"Rakan A. Alsowail","doi":"10.1002/dac.70071","DOIUrl":"https://doi.org/10.1002/dac.70071","url":null,"abstract":"<div>\u0000 \u0000 <p>Recently, the rapid expansion of blockchain technology has sparked a transformative wave across various sectors, prominently impacting cybersecurity. This paper introduces a pioneering intrusion detection model, the deep logic sparse autoencoder–based kookaburra search (DLSA-KS) algorithm. This innovative approach amalgamates advanced deep learning capabilities with an efficient initial search strategy, significantly enhancing the identification and mitigation of malicious activities within digital environments. The initial phase involves gathering input data from diverse datasets, including the Malware Executable Detection dataset, KDD Cup 1999 dataset, NSL-KDD dataset, Bot-IoT dataset, and UNSW-NB15 dataset. These datasets serve as foundational resources for training and evaluating the DLSA-KS model, ensuring its efficacy across varied cyber threat scenarios. This integration not only bolsters security but also enhances scalability and real-time detection capabilities, crucial for managing the voluminous data dynamics inherent in blockchain ecosystems. Moreover, the DLSA-KS model exhibits remarkable flexibility and optimization abilities, adapting proficiently to diverse network conditions. This adaptability contributes significantly to its overall performance, enabling robust intrusion detection across a spectrum of operational environments. In addition to this, the proposed DLSA-KS approach is evaluated across multiple performance metrics, including accuracy rate, detection rate, error rate, precision, and F-measure. The findings unequivocally demonstrate the model's superiority over existing methodologies, achieving exceptional metrics such as an accuracy rate of 98.7%, detection rate of 99.2%, error rate of 3%, precision of 97.8%, and F-measure of 98.7%. Thus, the results underscore the efficacy of the DLSA-KS algorithm in effectively detecting and mitigating intrusions, thereby affirming its potential as a pivotal advancement in cybersecurity defenses.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 7","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787279","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":"High-Gain 16-Port mm-Wave MIMO Antenna With Spiral-Shaped Electromagnetic Band Gap for 5G Applications","authors":"Nallagundla Suresh Babu,&nbsp;Sachin Kumar,&nbsp;Abdul Quaiyum Ansari,&nbsp;Binod Kumar Kanaujia,&nbsp;Bhawna Goyal,&nbsp;Torki Altameem,&nbsp;Walid El-Shafai","doi":"10.1002/dac.70074","DOIUrl":"https://doi.org/10.1002/dac.70074","url":null,"abstract":"<div>\u0000 \u0000 <p>A compact high-gain 16-port multiple-input-multiple-output (MIMO) antenna with a double spiral arm electromagnetic band gap (EBG) array is presented for 5G wireless networking applications. Each resonator of the proposed MIMO antenna consists of a microstrip line feeding, a fork-like monopole, and a partial ground plane. An array of EBG unit cells is positioned beneath the antenna elements to increase gain while decreasing surface wave effects, resulting in improved isolation among the resonating elements. The −10-dB impedance bandwidth of the trapezium-shaped monopole antenna element with EBG is 13.6 GHz (20.6–34.2 GHz) and isolation of &gt; 54 dB. The peak gain of the double spiral arm EBG-based antenna is 24.4 dB. The presented trapezium-shaped mm-wave MIMO antenna offers decent diversity proficiency metrics like envelope correlation coefficient (&lt; 0.26), directive gain (~10 dB), and total active reflection coefficient (&lt; −27.5 dB). The overall size of the presented 16-port mm-wave MIMO antenna is 43.5 mm × 43.5 mm and can be used for n257/n258/n261 5G wireless systems.</p>\u0000 </div>","PeriodicalId":13946,"journal":{"name":"International Journal of Communication Systems","volume":"38 7","pages":""},"PeriodicalIF":1.7,"publicationDate":"2025-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143787308","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}