{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T06:39:04Z","timestamp":1776926344091,"version":"3.51.2"},"reference-count":30,"publisher":"Tech Science Press","issue":"3","license":[{"start":{"date-parts":[[2025,8,3]],"date-time":"2025-08-03T00:00:00Z","timestamp":1754179200000},"content-version":"vor","delay-in-days":214,"URL":"https:\/\/doi.org\/10.32604\/TSP-CROSSMARKPOLICY"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["CMC"],"published-print":{"date-parts":[[2025]]},"DOI":"10.32604\/cmc.2025.065860","type":"journal-article","created":{"date-parts":[[2025,7,4]],"date-time":"2025-07-04T03:54:28Z","timestamp":1751601268000},"page":"5427-5443","update-policy":"https:\/\/doi.org\/10.32604\/tsp-crossmarkpolicy","source":"Crossref","is-referenced-by-count":0,"title":["Resource Allocation in V2X Networks: A Double Deep Q-Network Approach with Graph Neural Networks"],"prefix":"10.32604","volume":"84","author":[{"given":"Zhengda","family":"Huan","sequence":"first","affiliation":[]},{"given":"Jian","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Zeyu","family":"Chen","sequence":"additional","affiliation":[]},{"given":"Ziyi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Xiao","family":"Sun","sequence":"additional","affiliation":[]},{"given":"Zenghui","family":"Xiao","sequence":"additional","affiliation":[]}],"member":"17807","published-online":{"date-parts":[[2025]]},"reference":[{"key":"ref1","first-page":"100638","article-title":"Revolutionizing intelligent transportation systems with Cellular Vehicle-to-Everything (C-V2X) technology: current trends, use cases, emerging technologies, standardization bodies, industry analytics and future directions","volume":"43","author":"Dhinesh Kumar","year":"2023","journal-title":"Veh Commun"},{"key":"ref2","doi-asserted-by":"crossref","first-page":"1023","DOI":"10.1109\/JSAC.2023.3242723","article-title":"Radio resource management for C-V2X: from a hybrid centralized-distributed scheme to a distributed scheme","volume":"41","author":"Guo","year":"2023","journal-title":"IEEE J Sel Areas Commun"},{"key":"ref3","series-title":"2020 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom); 2020 May 26\u20132","first-page":"1","article-title":"QoS based deep reinforcement learning for V2X resource allocation","author":"Bhadauria"},{"key":"ref4","doi-asserted-by":"crossref","first-page":"2282","DOI":"10.1109\/JSAC.2019.2933962","article-title":"Spectrum sharing in vehicular networks based on multi-agent reinforcement learning","volume":"37","author":"Liang","year":"2019","journal-title":"IEEE J Sel Areas Commun"},{"key":"ref5","series-title":"2021 15th International Symposium on Medica0l Information and Communication Technology (ISMICT); 2021 Apr 14\u201316","first-page":"65","article-title":"Multi-agent reinforcement learning based channel access scheme for underwater optical wireless communication networks","author":"Zhang"},{"key":"ref6","doi-asserted-by":"crossref","first-page":"30014","DOI":"10.1109\/JIOT.2024.3410098","article-title":"Energy-efficient resource allocation for V2X communications","volume":"11","author":"Xu","year":"2024","journal-title":"IEEE Internet Things J"},{"key":"ref7","doi-asserted-by":"crossref","first-page":"4343","DOI":"10.1109\/TNSM.2024.3400605","article-title":"Energy efficient resource allocation framework based on dynamic meta-transfer learning for V2X communications","volume":"21","author":"Sohaib","year":"2024","journal-title":"IEEE Trans Netw Serv Manag"},{"key":"ref8","doi-asserted-by":"crossref","first-page":"1280","DOI":"10.1109\/COMST.2022.3149714","article-title":"A survey of collaborative machine learning using 5G vehicular communications","volume":"24","author":"Balkus","year":"2022","journal-title":"IEEE Commun Surv Tutor"},{"key":"ref9","doi-asserted-by":"crossref","first-page":"24138","DOI":"10.1007\/s11227-024-06383-4","article-title":"A resource optimization scheduling model and algorithm for heterogeneous computing clusters based on GNN and RL","volume":"80","author":"Zhang","year":"2024","journal-title":"J Supercomput"},{"key":"ref10","doi-asserted-by":"crossref","first-page":"11120","DOI":"10.1109\/TVT.2022.3187377","article-title":"Intelligent resource allocation in joint radar-communication with graph neural networks","volume":"71","author":"Lee","year":"2022","journal-title":"IEEE Trans Veh Technol"},{"key":"ref11","first-page":"1","article-title":"ICGNN: graph neural network enabled scalable beamforming for MISO interference channels","author":"He","year":"2025","journal-title":"IEEE Trans Mob Comput"},{"key":"ref12","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.ins.2022.05.090","article-title":"Underestimation estimators to Q-learning","volume":"607","author":"Abliz","year":"2022","journal-title":"Inf Sci"},{"key":"ref13","first-page":"1","article-title":"Enhancing channel selection in 5G with decentralized federated multi-agent deep reinforcement learning","volume":"7","author":"Shahgholi","year":"2024","journal-title":"Comput Knowl Eng"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"6380","DOI":"10.1109\/JIOT.2019.2962715","article-title":"Deep-reinforcement-learning-based mode selection and resource allocation for cellular V2X communications","volume":"7","author":"Zhang","year":"2020","journal-title":"IEEE Internet Things J"},{"key":"ref15","doi-asserted-by":"crossref","first-page":"2185","DOI":"10.1109\/TITS.2018.2865173","article-title":"A novel low-latency V2V resource allocation scheme based on cellular V2X communications","volume":"20","author":"Abbas","year":"2018","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"ref16","series-title":"2024 IEEE 6th International Conference on Power, Intelligent Computing and Systems (ICPICS); 2024 Jul 26\u201328","first-page":"964","article-title":"Research on graph feature aggregation algorithm based on GCN and GAT","author":"Zhou"},{"key":"ref17","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.neunet.2022.02.029","article-title":"A self-learning cognitive architecture exploiting causality from rewards","volume":"150","author":"Li","year":"2022","journal-title":"Neural Netw"},{"key":"ref18","series-title":"Applications of Computing, Automation and Wireless Systems in Electrical Engineering: Proceedings of MARC 2018","first-page":"873","article-title":"Comparative study of convolution neural network\u2019s ReLU and leaky-ReLU activation functions","author":"Dubey","year":"2019"},{"key":"ref19","doi-asserted-by":"crossref","first-page":"2622","DOI":"10.3390\/s23052622","article-title":"Dynamic spectrum sharing based on deep reinforcement learning in mobile communication systems","volume":"23","author":"Liu","year":"2023","journal-title":"Sensors"},{"key":"ref20","doi-asserted-by":"crossref","first-page":"1239","DOI":"10.1109\/COMST.2015.2420686","article-title":"Markov decision processes with applications in wireless sensor networks: a survey","volume":"17","author":"Alsheikh","year":"2015","journal-title":"IEEE Commun Surv Tutor"},{"key":"ref21","doi-asserted-by":"crossref","first-page":"3613","DOI":"10.1109\/JIOT.2024.3469547","article-title":"Graph neural networks and deep reinforcement learning based resource allocation for V2X communications","volume":"12","author":"Ji","year":"2024","journal-title":"IEEE Internet Things J"},{"key":"ref22","first-page":"100543","article-title":"Joint spectrum allocation and power control in vehicular communications based on dueling double DQN","volume":"38","author":"Ren","year":"2022","journal-title":"Veh Commun"},{"key":"ref23","first-page":"100895","article-title":"Resource allocation strategy for vehicular communication networks based on multi-agent deep reinforcement learning","volume":"53","author":"Liu","year":"2025","journal-title":"Veh Commun"},{"key":"ref24","doi-asserted-by":"crossref","first-page":"11624","DOI":"10.1109\/TVT.2022.3189627","article-title":"Intelligent surface aided D2D-V2X system for low-latency and high-reliability communications","volume":"71","author":"Gu","year":"2022","journal-title":"IEEE Trans Veh Technol"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"4408","DOI":"10.1109\/TVT.2024.3493137","article-title":"DDQN-based centralized spectrum allocation and distributed power control for V2X communications","volume":"74","author":"Liu","year":"2025","journal-title":"IEEE Trans Veh Technol"},{"key":"ref26","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3433000","article-title":"Network representation learning: from preprocessing, feature extraction to node embedding","volume":"55","author":"Zhou","year":"2022","journal-title":"ACM Comput Surv"},{"key":"ref27","unstructured":"3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); Further Advancements for E-UTRA Physical Layer Aspects (Release 9). [Internet]. [cited 2025 Jun 11]. Available from: https:\/\/api.semanticscholar.org\/CorpusID:16652630."},{"key":"ref28","doi-asserted-by":"crossref","first-page":"3163","DOI":"10.1109\/TVT.2019.2897134","article-title":"Deep reinforcement learning based resource allocation for V2V communications","volume":"68","author":"Ye","year":"2019","journal-title":"IEEE Trans Veh Technol"},{"key":"ref29","doi-asserted-by":"crossref","first-page":"5816","DOI":"10.1109\/LRA.2021.3074883","article-title":"Integrated task assignment and path planning for capacitated multi-agent pickup and delivery","volume":"6","author":"Chen","year":"2021","journal-title":"IEEE Robot Autom Lett"},{"key":"ref30","doi-asserted-by":"crossref","first-page":"3850","DOI":"10.1109\/TVT.2023.3326877","article-title":"A distributed multi-agent deep reinforcement learning-aided transmission design for dynamic vehicular communication networks","volume":"73","author":"Qu","year":"2023","journal-title":"IEEE Trans Veh Technol"}],"container-title":["Computers, Materials &amp; Continua"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/cdn.techscience.cn\/files\/cmc\/2025\/TSP_CMC-84-3\/TSP_CMC_65860\/TSP_CMC_65860.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,23]],"date-time":"2026-04-23T05:45:31Z","timestamp":1776923131000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.techscience.com\/cmc\/v84n3\/63172"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"references-count":30,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2025]]},"published-print":{"date-parts":[[2025]]}},"URL":"https:\/\/doi.org\/10.32604\/cmc.2025.065860","relation":{},"ISSN":["1546-2226"],"issn-type":[{"value":"1546-2226","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"2025-03-23","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-06-12","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2025-07-30","order":2,"name":"published","label":"Published Online","group":{"name":"publication_history","label":"Publication History"}}]}}