Journal of Communications and Networks最新文献

{"title":"CrossGuardian: A security domain isolation model for cross-chain gateway","authors":"Haosu Cheng;Guanquan Shi;Kangkang Zhang","doi":"10.23919/JCN.2025.000037","DOIUrl":"https://doi.org/10.23919/JCN.2025.000037","url":null,"abstract":"Blockchain, as a distributed ledger technology, embodies decentralization, security transparency, and traceability. Interoperability has been a persistent challenge in blockchain technology research. The inherent characteristics of blockchain, including numerous terminal nodes, diverse network architectures, cross-chain application services, and intricate network environments, present significant privacy and data security concerns for cross-chain gateways during data collection and transmission. To address these security challenges, this paper proposes a system architecture and security domain isolation model for cross-chain security gateways leveraging system resource virtualization. This architecture aims to address security issues encountered in the process of collecting, transmitting, and exchanging data elements within the cross-chain gateway. Specifically, the proposed architecture isolates the different layers in the cross-chain gateway by business domains, and ensures mutual security isolation between distinct business domains and network domains during cross-chain activities. Moreover, the paper implements a secure gateway operational environment utilizing x86 hardware platforms and virtualization technology, followed by simulation experiment and performance testing to validate the architectural feasibility. Formal proof is provided to establish the security of the proposed domain model.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"310-326"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142616","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A probabilistic alternative to coverage analysis in uniform random wireless networks","authors":"Junaid Farooq;Unnikrishna Pillai","doi":"10.23919/JCN.2025.000034","DOIUrl":"https://doi.org/10.23919/JCN.2025.000034","url":null,"abstract":"The analysis of coverage probability based on signal-to-interference-plus-noise-ratio (SINR) is a classical problem in the study of wireless and cellular networks. Stochastic geometry (SG) has opened up the possibility of accurate coverage characterization for random spatial deployment of base stations. While results obtained using SG are tractable and compact, in most cases, they are usually in the form of incomplete integrals, which need to be efficiently computed. Although that is possible with the computational capabilities available today, it masks the underlying structure in the analysis precluding the possibility of using it for solving optimization and system design problems. This paper provides an alternate approach to analyzing SINR-based coverage probability using direct probability computation. We analyze a uniformly random wireless network as a test case and compare the analytical results with widely accepted frameworks in the SG literature. Our analytical derivations, validated through simulation studies, agree with well-known results in the literature. The developed approach provides the groundwork for coverage analysis in more complex network scenarios and channel conditions.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"282-297"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142613","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"QNN framework based multiclass classification for downlink NOMA detectors","authors":"Hye Yeong Lee;Man Hee Lee;Soo Young Shin","doi":"10.23919/JCN.2025.000045","DOIUrl":"https://doi.org/10.23919/JCN.2025.000045","url":null,"abstract":"Quantum neural networks (QNNs) have attracted significant attention recently, primarily because of their potential to address complex problems deemed difficult for traditional computational methods. This study explores the viability of QNN in handling multiclass classification tasks in downlink nonorthogonal multiple access (NOMA) frameworks. The investigation includes a design of QNN framework and performance evaluation of a QNN-based NOMA detector, integrating maximum likelihood (ML), successive interference cancellation (SIC), and rotated ML (RML) methods. A QNN framework was configured for all three detectors, and a comparative analysis was conducted in terms of loss, accuracy, and testing across varied signal-to-noise ratio (SNR) levels and power allocation coefficients, considering NOMA-specific characteristics. Furthermore, the computational complexity of each detector was analyzed within the proposed framework.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"231-240"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142625","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904864","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Open access publishing agreement","authors":"","doi":"10.23919/JCN.2025.000067","DOIUrl":"https://doi.org/10.23919/JCN.2025.000067","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"279-281"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142621","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Stabilized classification control using multi-stage quantum convolutional neural networks for autonomous driving","authors":"Emily Jimin Roh;Soohyun Park;Soyi Jung;Joongheon Kim","doi":"10.23919/JCN.2025.000021","DOIUrl":"https://doi.org/10.23919/JCN.2025.000021","url":null,"abstract":"Real-time processing with high classification accuracy is a fundamental requirement in autonomous driving systems. However, existing neural network models for classification often face a tradeoff between computational efficiency and accuracy, necessitating the development of advanced optimization methods to address this limitation. Additionally, dynamic driving environments offer opportunities to enhance classification performance by leveraging the principles of quantum computing, particularly the properties of superposition and entanglement. In response to these challenges, a multi-stage quantum convolutional neural network (MS-QCNN) approach is proposed, designed to improve image analysis performance by effectively utilizing the multi-stage structure of QCNN. A Lyapunov optimization framework is applied to achieve optimal performance, which maximizes time-averaged efficiency while ensuring system stability. This framework dynamically adjusts the MS-QCNN model in response to environmental variations, promoting enhanced queue stability and achieving optimal time-averaged performance.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"264-272"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142618","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904869","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-modal sensing-assisted beam prediction using real-world dataset","authors":"Yerin Yeo;Junghyun Kim;Jihyung Kim;Junhwan Lee","doi":"10.23919/JCN.2025.000049","DOIUrl":"https://doi.org/10.23919/JCN.2025.000049","url":null,"abstract":"This paper explores techniques for beam prediction using multi-modal sensing data. Specifically, our aim is to develop a deep learning model that predicts the optimal beam using information collected from camera, LiDAR, radar, and GPS sensors. For this purpose, we propose ResNet-SE, which integrates a squeeze-and-excitation network with ResNet, and PIformer, a transformer-based model we design using pooling layers and inception mixer modules. Experimental results demonstrate a 22% improvement in prediction accuracy and a 38% reduction in training time compared to the state-of-the-art model.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"412-419"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142617","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533046","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Phase matching in Grover-QAOA for solving 3-SAT problems","authors":"Youngjin Seo;Jun Heo","doi":"10.23919/JCN.2025.000038","DOIUrl":"https://doi.org/10.23919/JCN.2025.000038","url":null,"abstract":"The Quantum Approximate Optimization Algorithm (QAOA) is a promising framework for combinatorial optimization, yet its performance is often hindered by the complexity of parameter optimization. In this work, we investigate phase relationships in Grover-QAOA (G-QAOA) for solving 3-SAT problems and introduce a novel phase matching condition that simplifies the optimization landscape. By aligning the phases of the problem and mixing Hamiltonians, our approach reduces the number of variational parameters from 2p to p, significantly lowering computational overhead. We further propose single-angle G-QAOA, an extension that enables additional parameter reduction. Numerical simulations demonstrate that our method achieves success probabilities comparable to those of standard G-QAOA while requiring fewer quantum circuit evaluations. These results highlight the potential of our proposed G-QAOA for practical implementation on near-term quantum hardware.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"222-230"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142622","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Special issue on quantum technologies for communication systems","authors":"Soo Young Shin;Zhu Han;Shaukat Ali;Samuel Yen-Chi Chen;Yuanwei Liu;Soohyun Park;Joongheon Kim","doi":"10.23919/JCN.2025.000064","DOIUrl":"https://doi.org/10.23919/JCN.2025.000064","url":null,"abstract":"Quantum technologies hold the potential to revolutionize classical technologies and their emerging applications in communication networks and mobility. This potential is expected to grow alongside the advancement of quantum computation-capable devices. Currently, quantum devices are at the noisy intermediate-scale quantum (NISQ) level and can support only a few hundred physical qubits. While these devices remain constrained in scale, early fault-tolerant quantum hardware is capable of demonstrating the quantum advantage, the ability to outperform classical counterparts in specific computational tasks. This capability is essential for enhancing coordination of autonomous and distributed systems, such as low Earth orbit (LEO) satellites, autonomous driving vehicles, and complex infrastructure required by the hyper-connected 6G communication networks. Especially in artificial intelligence (AI) research domains, parameterized quantum circuits used in quantum algorithms, quantum optimization, and quantum machine learning (QML), can implement various functionalities of classical neural network architectures with significantly fewer parameters and computation resources. This can substantially reduce the latency and memory constraints of current large-scale classical neural network frameworks, including diffusion-based generative computer vision algorithms and large language models. According to the current roadmaps for quantum computer development, the number of qubits is expected to greatly increase, and the beyond-NISQ era is set to emerge approximately by 2026. This highlights the need for early contributions to explore the potential impact of quantum algorithms and QML on emerging communication system design and future applications. Towards unleashing the full potential of quantum algorithms and QML, this special issue focuses on quantum algorithms and QML principles, algorithms, and use cases to seek original contributions to various aspects of QML-based system architectures, protocols, resource management, error correction, and other technologies in communication systems. Furthermore, there is also an increasing interest in applying classical AI techniques for solving problems within quantum computing and computation, such as in quantum software engineering, quantum circuit design, and optimizing quantum optimization algorithms. Despite significant interest in this field from both academia and industry, many important questions remain. This special issue of JCN presents five high-quality papers which are categorized under (i) theory, (ii) communications and networks, and (iii) applications. In the following, we will introduce the topic section categories and corresponding papers included in this Special Issue.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"217-221"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142609","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An energy-density-based trajectory planning method for wireless sensor networks with mobile collectors","authors":"Hongmei Wang;Heejung Byun","doi":"10.23919/JCN.2025.000022","DOIUrl":"https://doi.org/10.23919/JCN.2025.000022","url":null,"abstract":"Mobile collectors (MCs), such as unmanned aerial vehicles (UAVs), play a crucial role in conserving energy and enhancing the longevity of wireless sensor networks (WSNs) compared to static sinks. The implementation of efficient routing algorithms and scheduling mechanisms tailored for MCs is of utmost importance. In response to this challenge, we propose an innovative data collection method called energy- density-based trajectory planning (EDTP) specifically designed for WSNs equipped with MCs. First, we introduce a global energy-difference density optimization scheme (GEDD) to select cluster heads (CHs) responsible for transmitting data to MCs. The selection of CHs aims to balance the energy consumption of nodes, thereby extending the system's lifespan. Second, we propose the K-dimension tree grouping algorithm (KDTG) with high computational efficiency to group CHs based on their geographical similarity. Comparisons with three existing approaches demonstrate that our proposed EDTP method can significantly increase system lifetime and reduce latency.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 3","pages":"190-199"},"PeriodicalIF":3.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11106371","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751071","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint offloading and resource allocation based on Lyapunov algorithm in delay-sensitive SAGIN","authors":"Jingjing Du;Lei Xiong;Dan Fei;Liang Shen;Xiangbing Tan","doi":"10.23919/JCN.2025.000033","DOIUrl":"https://doi.org/10.23919/JCN.2025.000033","url":null,"abstract":"The integration of mobile edge computing (MEC) and space-air-ground integrated network (SAGIN) can significantly reduce the user's task processing delay, while relieving the data pressure on the core network, so as to meet the performance requirements of computation capability, throughput, and delay brought about by the massive connectivity of SAGIN, which is an important direction for current research on 6G networks. In this study, we focus on optimizing user delay and usage costs within the SAGIN framework, which comprises low Earth orbit (LEO) satellites, high altitude balloons (HAB), and ground users. Specifically, ground users adopt a partial offloading strategy, wherein computational tasks are offloaded via HABs to MEC servers hosted by LEO satellites for processing. To accommodate the highly dynamic nature of the satellite constellation, we formulate an optimization problem aimed at maximizing the long-term time-averaged latency while minimizing costs, and introduce the Lyapunov optimization method to solve it. The simulation results demonstrate that our proposed algorithm can effectively reduce the network latency and user's usage cost, while ensuring system stability.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 3","pages":"166-178"},"PeriodicalIF":3.2,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11106372","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144751072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}