Pub Date : 2025-10-01DOI: 10.23919/JCN.2025.000078
{"title":"Information for authors","authors":"","doi":"10.23919/JCN.2025.000078","DOIUrl":"https://doi.org/10.23919/JCN.2025.000078","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"421-425"},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11251111","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533055","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}
Pub Date : 2025-10-01DOI: 10.23919/JCN.2025.000079
{"title":"Open access publishing agreement","authors":"","doi":"10.23919/JCN.2025.000079","DOIUrl":"https://doi.org/10.23919/JCN.2025.000079","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"426-428"},"PeriodicalIF":3.2,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11251107","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533045","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}
Pub Date : 2025-09-18DOI: 10.23919/JCN.2025.000053
Noor Hafsa;Hadeel Alzoubi;Sajida Imran
The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs). These attacks can disrupt network topologies and compromise data transmission. Early detection of routing attacks is crucial, particularly in resource-constrained RPL networks. This study employed a simulated dataset encompassing Hello Flood, Version Number, and Worst Parent attacks to develop a robust detection model for resource-based routing attacks in IoT networks. In this research, a novel cross-layer feature analysis was conducted, identifying 12 key features crucial for distinguishing between normal and malicious nodes within the network out of the 29 features examined. Various machine learning algorithms, including random forest, CatBoost, and extreme gradient boosting, were evaluated for precise classification. The optimized CatBoost model, a gradient-boosting decision tree (DT) algorithm, demonstrated outstanding performance with a 99% of detection rate, 0.8% of false positive rate, 98% of sensitivity, and 98% of positive predictive values on an independent test dataset. Furthermore, an advanced intrusion prevention algorithm leveraging cross-layer feature-induced intrusion detection was introduced to effectively combat prevalent routing attacks. This study significantly contributes to enhancing cybersecurity in IoT networks, particularly in smart cities, by offering robust intrusion detection and prevention mechanisms.
{"title":"Machine learning-based intrusion detection and prevention using cross-layer features in Internet of Things (IoT) networks","authors":"Noor Hafsa;Hadeel Alzoubi;Sajida Imran","doi":"10.23919/JCN.2025.000053","DOIUrl":"https://doi.org/10.23919/JCN.2025.000053","url":null,"abstract":"The IoT has emerged as a significant target for cyber-attacks, particularly with a focus on the routing protocol for low-power and lossy networks (RPL) within Wireless Sensor Networks (WSNs). These attacks can disrupt network topologies and compromise data transmission. Early detection of routing attacks is crucial, particularly in resource-constrained RPL networks. This study employed a simulated dataset encompassing Hello Flood, Version Number, and Worst Parent attacks to develop a robust detection model for resource-based routing attacks in IoT networks. In this research, a novel cross-layer feature analysis was conducted, identifying 12 key features crucial for distinguishing between normal and malicious nodes within the network out of the 29 features examined. Various machine learning algorithms, including random forest, CatBoost, and extreme gradient boosting, were evaluated for precise classification. The optimized CatBoost model, a gradient-boosting decision tree (DT) algorithm, demonstrated outstanding performance with a 99% of detection rate, 0.8% of false positive rate, 98% of sensitivity, and 98% of positive predictive values on an independent test dataset. Furthermore, an advanced intrusion prevention algorithm leveraging cross-layer feature-induced intrusion detection was introduced to effectively combat prevalent routing attacks. This study significantly contributes to enhancing cybersecurity in IoT networks, particularly in smart cities, by offering robust intrusion detection and prevention mechanisms.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"345-358"},"PeriodicalIF":3.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11173243","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533052","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}
Pub Date : 2025-09-18DOI: 10.23919/JCN.2025.000052
Mahmoud A. Albreem;Saeed Abdallah;Mohamed Saad;Mahmoud Aldababsa;Khawla Alnajjar
Massive multiple-input multiple-output (mMIMO) plays a crucial role in improving the quality-of-service and achieving high power efficiency and spectrum efficiency in beyond fifth generation communication systems. However, data detection in uplink mMIMO is not a trivial task as the computational complexity increases with the number of antennas. The equalization matrix is diagonally dominant, and hence, most of the existing linear detectors use the diagonal matrix. Unfortunately, detection based on a diagonal matrix may require a high number of iterations to converge, which increases the computational complexity. This is highly challenging because of the large number of antennas on both the transmitting and receiving sides. In this paper, we propose a refinement of six linear mMIMO detectors based on a band matrix formulation to accelerate the convergence rate, and hence reduce the complexity. The proposed linear detectors include the Newton iterations method, the Neumann series method, the accelerated over-relaxation method, the successive over-relaxation method, the Gauss-Seidel (GS) method, and the Jacobi method. The computation of the band matrix inverse is also presented in this paper and employed in the proposed detectors. In addition, efficient initialization based on the structure of the band matrix is proposed, which both improves the convergence rate and yields a substantial performance gain. Simulations show that the proposed detectors achieve minimum mean-squared error performance with significant complexity reduction even when the number of users approaches the number of base station antennas. It is also shown that the refined detector based on the GS and band matrix achieves the highest performance gain with the lowest computational complexity.
{"title":"Low complexity detectors for uplink massive MIMO based on a refinement of linear algorithms and efficient initialization","authors":"Mahmoud A. Albreem;Saeed Abdallah;Mohamed Saad;Mahmoud Aldababsa;Khawla Alnajjar","doi":"10.23919/JCN.2025.000052","DOIUrl":"https://doi.org/10.23919/JCN.2025.000052","url":null,"abstract":"Massive multiple-input multiple-output (mMIMO) plays a crucial role in improving the quality-of-service and achieving high power efficiency and spectrum efficiency in beyond fifth generation communication systems. However, data detection in uplink mMIMO is not a trivial task as the computational complexity increases with the number of antennas. The equalization matrix is diagonally dominant, and hence, most of the existing linear detectors use the diagonal matrix. Unfortunately, detection based on a diagonal matrix may require a high number of iterations to converge, which increases the computational complexity. This is highly challenging because of the large number of antennas on both the transmitting and receiving sides. In this paper, we propose a refinement of six linear mMIMO detectors based on a band matrix formulation to accelerate the convergence rate, and hence reduce the complexity. The proposed linear detectors include the Newton iterations method, the Neumann series method, the accelerated over-relaxation method, the successive over-relaxation method, the Gauss-Seidel (GS) method, and the Jacobi method. The computation of the band matrix inverse is also presented in this paper and employed in the proposed detectors. In addition, efficient initialization based on the structure of the band matrix is proposed, which both improves the convergence rate and yields a substantial performance gain. Simulations show that the proposed detectors achieve minimum mean-squared error performance with significant complexity reduction even when the number of users approaches the number of base station antennas. It is also shown that the refined detector based on the GS and band matrix achieves the highest performance gain with the lowest computational complexity.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"298-309"},"PeriodicalIF":3.2,"publicationDate":"2025-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11173246","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533054","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}
Pub Date : 2025-08-26DOI: 10.23919/JCN.2025.000036
Tingting Yang;Yingqi Zhao;Jin Jin;Kaiyang Guo
This paper considers device-to-device (D2D) communication underlaying cellular networks, where frequency resources are shared between D2D users and cellular users. When D2D users reuse the frequency resources occupied by the cellular users, interference could be produced among the two kinds of users. By means of the fractional frequency reuse approach, a traversal frequency reuse scheme is proposed, in which central D2D users in each cell reuse the frequency bands for neighbouring edge cellular users in sequence according to a counterclockwise direction. The proposed reuse scheme effectively minimizes the number of intra-cell interference links, leading to an improvement of the average sum rate. Subsequently, based on the proposed traversal reuse strategy, a deep Q-learning algorithm is implemented for power control. Simulation results demonstrate that the proposed power control algorithm outperforms other traditional methods in terms of sum rate.
{"title":"Power control for D2D communication underlaying cellular networks based on deep Q-learning and fractional frequency reuse","authors":"Tingting Yang;Yingqi Zhao;Jin Jin;Kaiyang Guo","doi":"10.23919/JCN.2025.000036","DOIUrl":"https://doi.org/10.23919/JCN.2025.000036","url":null,"abstract":"This paper considers device-to-device (D2D) communication underlaying cellular networks, where frequency resources are shared between D2D users and cellular users. When D2D users reuse the frequency resources occupied by the cellular users, interference could be produced among the two kinds of users. By means of the fractional frequency reuse approach, a traversal frequency reuse scheme is proposed, in which central D2D users in each cell reuse the frequency bands for neighbouring edge cellular users in sequence according to a counterclockwise direction. The proposed reuse scheme effectively minimizes the number of intra-cell interference links, leading to an improvement of the average sum rate. Subsequently, based on the proposed traversal reuse strategy, a deep Q-learning algorithm is implemented for power control. Simulation results demonstrate that the proposed power control algorithm outperforms other traditional methods in terms of sum rate.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"359-368"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142615","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533043","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}
Pub Date : 2025-08-26DOI: 10.23919/JCN.2025.000047
Cheol Hea Koo
Space networks face significant challenges establishing physical links due to uncertain node positions and heterogeneous communication systems, requiring pre-computed flight dynamics and higher readiness levels than terrestrial networks. This study introduces a visionary server, an authoritative ground-based management system generating pre-negotiated paths instead of relying on real-time computations by individual nodes. The server distributes routing information through a structured extension block for bundle protocol version 7, enabling contact establishment without prior knowledge of adjacent node characteristics. Qualitative simulations using realistic scenarios validate this concept's effectiveness. The key innovation lies in the dual-mode architecture combining centralized coordination with distributed failure detection, which: (i) reduces computational requirements by processing on ground, (ii) facilitates network trouble shoots through available routing information, and (iii) considers data rate, frequency, and modulation type while orchestrating routing decisions across heterogeneous space assets without requiring physical layer standardization.
{"title":"An architecture for bundle routing in space: Collaborative contact negotiation and visionary server for DTN route development","authors":"Cheol Hea Koo","doi":"10.23919/JCN.2025.000047","DOIUrl":"https://doi.org/10.23919/JCN.2025.000047","url":null,"abstract":"Space networks face significant challenges establishing physical links due to uncertain node positions and heterogeneous communication systems, requiring pre-computed flight dynamics and higher readiness levels than terrestrial networks. This study introduces a visionary server, an authoritative ground-based management system generating pre-negotiated paths instead of relying on real-time computations by individual nodes. The server distributes routing information through a structured extension block for bundle protocol version 7, enabling contact establishment without prior knowledge of adjacent node characteristics. Qualitative simulations using realistic scenarios validate this concept's effectiveness. The key innovation lies in the dual-mode architecture combining centralized coordination with distributed failure detection, which: (i) reduces computational requirements by processing on ground, (ii) facilitates network trouble shoots through available routing information, and (iii) considers data rate, frequency, and modulation type while orchestrating routing decisions across heterogeneous space assets without requiring physical layer standardization.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"327-344"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142620","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533053","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}
The quantum Internet is profoundly impacting the world and is expected to be operational in the future. With the global wide-area quantum networks begin to take shape, drone-based quantum entanglement networks have attracted widespread attention. Compared to quantum links based on optical fibers or satellites, drone-based quantum entanglement networks can effectively address the need for responsive and on-demand quantum network coverage across diverse locations and operational times. To realize network construction, entanglement routing protocols pose a significant challenge. On the one hand, the fidelity of the entangled system degrades hop-byhop. On the other hand, the dynamics and limited energy of drone nodes are equally not negligible. However, existing works have not adequately addressed these issues. In this paper, we present a novel fidelity-guaranteed entanglement routing protocol for drone-based quantum networks (FGER_D). The FGER_D considers the node energy and quantum link vulnerability comprehensively, selects end-to-end fidelity as the routing metric, and employs multiple attempts' entanglement purification scheme to provide fidelity-guaranteed entanglement connections in noisy environments. Numerical simulations demonstrate that compared to existing algorithms, FGER_D improves network throughput by approximately 24% under default settings, while also ensuring network fidelity and extending network lifetime. Our work is expected to provide a theoretical basis for the deployment of drone-based entanglement distribution networks.
{"title":"Entanglement routing with guaranteed fidelity for drone-based quantum networks","authors":"Haoran Hu;Huazhi Lun;Ya Wang;Zhifeng Deng;Jiahao Li;Jie Tang;Yuexiang Cao;Ying Liu;Dan Wu;Huicun Yu;Xingyu Wang;Jiahua Wei;Lei Shi","doi":"10.23919/JCN.2025.000046","DOIUrl":"https://doi.org/10.23919/JCN.2025.000046","url":null,"abstract":"The quantum Internet is profoundly impacting the world and is expected to be operational in the future. With the global wide-area quantum networks begin to take shape, drone-based quantum entanglement networks have attracted widespread attention. Compared to quantum links based on optical fibers or satellites, drone-based quantum entanglement networks can effectively address the need for responsive and on-demand quantum network coverage across diverse locations and operational times. To realize network construction, entanglement routing protocols pose a significant challenge. On the one hand, the fidelity of the entangled system degrades hop-byhop. On the other hand, the dynamics and limited energy of drone nodes are equally not negligible. However, existing works have not adequately addressed these issues. In this paper, we present a novel fidelity-guaranteed entanglement routing protocol for drone-based quantum networks (FGER_D). The FGER_D considers the node energy and quantum link vulnerability comprehensively, selects end-to-end fidelity as the routing metric, and employs multiple attempts' entanglement purification scheme to provide fidelity-guaranteed entanglement connections in noisy environments. Numerical simulations demonstrate that compared to existing algorithms, FGER_D improves network throughput by approximately 24% under default settings, while also ensuring network fidelity and extending network lifetime. Our work is expected to provide a theoretical basis for the deployment of drone-based entanglement distribution networks.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"241-251"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142614","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904870","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}
Pub Date : 2025-08-26DOI: 10.23919/JCN.2025.000008
Vuppula Roopa;Himansu Shekhar Pradhan
Future wireless communication networks are exploring the 0.1 to 10 terahertz (THz) band, which presents opportunities for creative usage. However, the management of growing privacy and security issues while allocating resources efficiently to support many devices is a critical activity. Complicated technology affects resource allocation (RA) and network management as it permeates devices and infrastructure. Upgrading from fifth-generation (5G) to next-generation represents breakthroughs in ultra-low latency, fast data speeds, and artificial intelligence (AI) integration for innovative services and applications. However, these developments convey the challenges that include data processing, RA, network administration, and privacy. Integrating blockchain (BC) as well as machine learning (ML) is a potential alternative to tackle these challenges. This paper presents a comprehensive review, which explores their combined contributions to trust, decentralization, and network security in ML decisions, immutability, and streamlined model sharing. Moreover, it delves into various areas such as rate splitting, next-generation radaroriented communication, BC-oriented spectrum reframing, reconfigurable intelligent surfaces (RIS), and integrated sensing and communication. In addition, it investigates using ML and BC in emerging next-generation communication technologies, which include semantic, molecular, and holographic communications. Finally, the authors deal with the essential unsolved issues, challenges, prospective solutions, and the wide range of opportunities for additional research in this rapidly evolving fields.
{"title":"Exploring blockchain and artificial intelligence for next generation wireless networks","authors":"Vuppula Roopa;Himansu Shekhar Pradhan","doi":"10.23919/JCN.2025.000008","DOIUrl":"https://doi.org/10.23919/JCN.2025.000008","url":null,"abstract":"Future wireless communication networks are exploring the 0.1 to 10 terahertz (THz) band, which presents opportunities for creative usage. However, the management of growing privacy and security issues while allocating resources efficiently to support many devices is a critical activity. Complicated technology affects resource allocation (RA) and network management as it permeates devices and infrastructure. Upgrading from fifth-generation (5G) to next-generation represents breakthroughs in ultra-low latency, fast data speeds, and artificial intelligence (AI) integration for innovative services and applications. However, these developments convey the challenges that include data processing, RA, network administration, and privacy. Integrating blockchain (BC) as well as machine learning (ML) is a potential alternative to tackle these challenges. This paper presents a comprehensive review, which explores their combined contributions to trust, decentralization, and network security in ML decisions, immutability, and streamlined model sharing. Moreover, it delves into various areas such as rate splitting, next-generation radaroriented communication, BC-oriented spectrum reframing, reconfigurable intelligent surfaces (RIS), and integrated sensing and communication. In addition, it investigates using ML and BC in emerging next-generation communication technologies, which include semantic, molecular, and holographic communications. Finally, the authors deal with the essential unsolved issues, challenges, prospective solutions, and the wide range of opportunities for additional research in this rapidly evolving fields.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 5","pages":"386-411"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142611","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145533048","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}
Pub Date : 2025-08-26DOI: 10.23919/JCN.2025.000066
{"title":"Information for authors","authors":"","doi":"10.23919/JCN.2025.000066","DOIUrl":"https://doi.org/10.23919/JCN.2025.000066","url":null,"abstract":"","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"274-278"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142606","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904774","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}
It is imperative to reduce carbon dioxide emissions and fossil fuel consumption to ensure the Earth's sustainable future and mitigate negative impacts like extreme climate changes caused by greenhouse gases. Electric vehicles (EVs) play a pivotal role in this context, where the convenience of charging stations is crucial in influencing consumer choices. This paper formulates the placement of charging stations as an optimization problem, considering factors like station density, accessibility, coverage, and regional cost variations, to minimize total construction costs. The problem is mapped onto a quadratic unconstrained binary optimization (QUBO) model. The QUBO can efficiently represent and solve complex combinatorial optimization problems, making it suitable for quantum and advanced classical algorithms. Utilizing digital quantum annealing, the optimal or near-optimal solutions are efficiently identified. The performance of the proposed approach is compared with classical algorithms, including mixed linear programming and simulated annealing, demonstrating significant advancements of digital annealing.
{"title":"Solving optimal electric vehicle charging station placement problem using digital quantum annealing","authors":"Chia-Ho Ou;Chung-Chieh Cheng;Chih-Yu Chen;Krischonme Bhumkittipich;Sillawat Romphochai","doi":"10.23919/JCN.2025.000048","DOIUrl":"https://doi.org/10.23919/JCN.2025.000048","url":null,"abstract":"It is imperative to reduce carbon dioxide emissions and fossil fuel consumption to ensure the Earth's sustainable future and mitigate negative impacts like extreme climate changes caused by greenhouse gases. Electric vehicles (EVs) play a pivotal role in this context, where the convenience of charging stations is crucial in influencing consumer choices. This paper formulates the placement of charging stations as an optimization problem, considering factors like station density, accessibility, coverage, and regional cost variations, to minimize total construction costs. The problem is mapped onto a quadratic unconstrained binary optimization (QUBO) model. The QUBO can efficiently represent and solve complex combinatorial optimization problems, making it suitable for quantum and advanced classical algorithms. Utilizing digital quantum annealing, the optimal or near-optimal solutions are efficiently identified. The performance of the proposed approach is compared with classical algorithms, including mixed linear programming and simulated annealing, demonstrating significant advancements of digital annealing.","PeriodicalId":54864,"journal":{"name":"Journal of Communications and Networks","volume":"27 4","pages":"252-263"},"PeriodicalIF":3.2,"publicationDate":"2025-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=11142623","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144904867","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}
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