{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T15:06:41Z","timestamp":1775228801806,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T00:00:00Z","timestamp":1720051200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61701197"],"award-info":[{"award-number":["61701197"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2021YFA1000500(4)"],"award-info":[{"award-number":["2021YFA1000500(4)"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["B23008"],"award-info":[{"award-number":["B23008"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"National Key Research and Development Program of China","award":["61701197"],"award-info":[{"award-number":["61701197"]}]},{"name":"National Key Research and Development Program of China","award":["2021YFA1000500(4)"],"award-info":[{"award-number":["2021YFA1000500(4)"]}]},{"name":"National Key Research and Development Program of China","award":["B23008"],"award-info":[{"award-number":["B23008"]}]},{"name":"111 project","award":["61701197"],"award-info":[{"award-number":["61701197"]}]},{"name":"111 project","award":["2021YFA1000500(4)"],"award-info":[{"award-number":["2021YFA1000500(4)"]}]},{"name":"111 project","award":["B23008"],"award-info":[{"award-number":["B23008"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>As autonomous driving may be the most important application scenario of the next generation, the development of wireless access technologies enabling reliable and low-latency vehicle communication becomes crucial. To address this, 3GPP has developed Vehicle-to-Everything (V2X) specifications based on 5G New Radio (NR) technology, where Mode 2 Side-Link (SL) communication resembles Mode 4 in LTE-V2X, allowing direct communication between vehicles. This supplements SL communication in LTE-V2X and represents the latest advancements in cellular V2X (C-V2X) with the improved performance of NR-V2X. However, in NR-V2X Mode 2, resource collisions still occur and thus degrade the age of information (AOI). Therefore, an interference cancellation method is employed to mitigate this impact by combining NR-V2X with Non-Orthogonal multiple access (NOMA) technology. In NR-V2X, when vehicles select smaller resource reservation intervals (RRIs), higher-frequency transmissions use more energy to reduce AoI. Hence, it is important to jointly considerAoI and communication energy consumption based on NR-V2X communication. Then, we formulate such an optimization problem and employ the Deep Reinforcement Learning (DRL) algorithm to compute the optimal transmission RRI and transmission power for each transmitting vehicle to reduce the energy consumption of each transmitting vehicle and the AoI of each receiving vehicle. Extensive simulations demonstrate the performance of our proposed algorithm.<\/jats:p>","DOI":"10.3390\/s24134338","type":"journal-article","created":{"date-parts":[[2024,7,4]],"date-time":"2024-07-04T03:52:58Z","timestamp":1720065178000},"page":"4338","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Joint Optimization of Age of Information and Energy Consumption in NR-V2X System Based on Deep Reinforcement Learning"],"prefix":"10.3390","volume":"24","author":[{"given":"Shulin","family":"Song","sequence":"first","affiliation":[{"name":"School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China"},{"name":"Zhuhai Fudan Innovation Institute, Zhuhai 519031, China"}]},{"given":"Zheng","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China"},{"name":"Zhuhai Fudan Innovation Institute, Zhuhai 519031, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4899-1718","authenticated-orcid":false,"given":"Qiong","family":"Wu","sequence":"additional","affiliation":[{"name":"School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China"},{"name":"Zhuhai Fudan Innovation Institute, Zhuhai 519031, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0658-6079","authenticated-orcid":false,"given":"Pingyi","family":"Fan","sequence":"additional","affiliation":[{"name":"Department of Electronic Engineering, Beijing National Research Center for Information Science and Technology, Tsinghua University, Beijing 100084, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4940-7453","authenticated-orcid":false,"given":"Qiang","family":"Fan","sequence":"additional","affiliation":[{"name":"Qualcomm, San Jose, CA 95110, USA"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2012","DOI":"10.1109\/TNSM.2023.3322881","article-title":"Delay-Sensitive Task Offloading in Vehicular Fog Computing-Assisted Platoons","volume":"21","author":"Wu","year":"2024","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"799","DOI":"10.1007\/s11276-015-1000-6","article-title":"Performance modeling and analysis of the ADHOC MAC protocol for vehicular networks","volume":"22","author":"Wu","year":"2016","journal-title":"Wirel. Netw."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3000","DOI":"10.1109\/TWC.2008.060831","article-title":"A unified cross-layer framework for resource allocation in cooperative networks","volume":"7","author":"Chen","year":"2008","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"2949","DOI":"10.1109\/ICC.2004.1313070","article-title":"Adaptive resource allocation and scheduling for multiuser packet-based OFDM networks","volume":"Volume 5","author":"Zhang","year":"2004","journal-title":"Proceedings of the 2004 IEEE International Conference on Communications (IEEE Cat. No. 04CH37577)"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Wu, Q., Wang, W., Fan, P., Fan, Q., Wang, J., and Letaief, K.B. (2024). URLLC-Awared Resource Allocation for Heterogeneous Vehicular Edge Computing. IEEE Trans. Veh. Technol., 1\u201316.","DOI":"10.1109\/TVT.2024.3370196"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.23919\/JCC.2023.03.001","article-title":"High stable and accurate vehicle selection scheme based on federated edge learning in vehicular networks","volume":"20","author":"Wu","year":"2023","journal-title":"China Commun."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"V1-370","DOI":"10.1109\/ICINA.2010.5636371","article-title":"Optimal deployment of wireless mesh sensor networks based on Delaunay triangulations","volume":"Volume 1","author":"Jing","year":"2010","journal-title":"Proceedings of the 2010 International Conference on Information, Networking and Automation (ICINA)"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1230","DOI":"10.23919\/cje.2022.00.093","article-title":"Towards V2I age-aware fairness access: A DQN based intelligent vehicular node training and test method","volume":"32","author":"Qiong","year":"2023","journal-title":"Chin. J. Electron."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1109\/JSTSP.2022.3221271","article-title":"Mobility-aware cooperative caching in vehicular edge computing based on asynchronous federated and deep reinforcement learning","volume":"17","author":"Wu","year":"2022","journal-title":"IEEE J. Sel. Top. Signal Process."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Wu, Q., Wang, W., Fan, P., Fan, Q., Zhu, H., and Letaief, K.B. (2024). Cooperative Edge Caching Based on Elastic Federated and Multi-Agent Deep Reinforcement Learning in Next-Generation Networks. IEEE Trans. Netw. Serv. Manag., 1.","DOI":"10.1109\/TNSM.2024.3403842"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Tlake, L.C., Markus, E.D., and Abu-Mahfouz, A.M. (2021, January 13\u201315). A Review of Interference Challenges on Integrated 5GNR and NB-IoT Networks. Proceedings of the 2021 IEEE AFRICON, Arusha, Tanzania.","DOI":"10.1109\/AFRICON51333.2021.9570861"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1972","DOI":"10.1109\/COMST.2021.3057017","article-title":"A Tutorial on 5G NR V2X Communications","volume":"23","author":"Garcia","year":"2021","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"3169","DOI":"10.1109\/COMST.2018.2860778","article-title":"Integrated Data and Energy Communication Network: A Comprehensive Survey","volume":"20","author":"Hu","year":"2018","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wijerathna Basnayaka, C.M., Jayakody, D.N.K., Ponnimbaduge Perera, T.D., and Vidal Ribeiro, M. (2021, January 25\u201328). Age of Information in an URLLC-enabled Decode-and-Forward Wireless Communication System. Proceedings of the 2021 IEEE 93rd Vehicular Technology Conference (VTC2021-Spring), Virtual Event.","DOI":"10.1109\/VTC2021-Spring51267.2021.9449007"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"5690","DOI":"10.1109\/TVT.2023.3332905","article-title":"An Efficient Caching and Offloading Resource Allocation Strategy in Vehicular Social Networks","volume":"73","author":"Zhang","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Rehman, A., Valentini, R., Cinque, E., Di Marco, P., and Santucci, F. (2023). On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications. Sensors, 23.","DOI":"10.3390\/s23104901"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Anwar, W., Franchi, N., and Fettweis, G. (2019, January 22\u201325). Physical layer evaluation of V2X communications technologies: 5G NR-V2X, LTE-V2X, IEEE 802.11 bd, and IEEE 802.11 p. Proceedings of the 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA.","DOI":"10.1109\/VTCFall.2019.8891313"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Gong, J., Chen, X., and Ma, X. (2018, January 9\u201313). Energy-age tradeoff in status update communication systems with retransmission. Proceedings of the 2018 IEEE Global Communications Conference (GLOBECOM), Abu Dhabi, United Arab Emirates.","DOI":"10.1109\/GLOCOM.2018.8647730"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5324","DOI":"10.1109\/JIOT.2019.2900528","article-title":"Timely status update in Internet of Things monitoring systems: An age-energy tradeoff","volume":"6","author":"Gu","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"8748","DOI":"10.1109\/JIOT.2020.2996562","article-title":"Application-oriented scheduling for optimizing the age of correlated information: A deep-reinforcement-learning-based approach","volume":"7","author":"Yin","year":"2020","journal-title":"IEEE Internet Things J."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Liang, H., Wang, L., Zhang, Y., Shan, H., and Shi, Z. (2023, January 10\u201312). Extending 5G NR V2X Mode 2 to Enable Integrated Sensing and Communication for Vehicular Networks. Proceedings of the 2023 IEEE\/CIC International Conference on Communications in China (ICCC Workshops), Dalian, China.","DOI":"10.1109\/ICCCWorkshops57813.2023.10233829"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"73164","DOI":"10.1109\/ACCESS.2020.2983715","article-title":"Maximum-throughput sidelink resource allocation for NR-V2X networks with the energy-efficient CSI transmission","volume":"8","author":"Xiaoqin","year":"2020","journal-title":"IEEE Access"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2669","DOI":"10.1109\/TVT.2023.3318235","article-title":"On the Impact of Re-evaluation in 5G NR V2X Mode 2","volume":"73","author":"Lusvarghi","year":"2024","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Soleymani, D.M., Ravichandran, L., Gholami, M.R., Del Galdo, G., and Harounabadi, M. (2021, January 13\u201316). Energy-efficient autonomous resource selection for power-saving users in NR V2X. Proceedings of the 2021 IEEE 32nd Annual International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC), Helsinki, Finland.","DOI":"10.1109\/PIMRC50174.2021.9569365"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"87225","DOI":"10.1109\/ACCESS.2023.3305267","article-title":"Radio resource allocation in 5G-NR V2X: A multi-agent actor-critic based approach","volume":"11","author":"Hegde","year":"2023","journal-title":"IEEE Access"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Saad, M.M., Tariq, M.A., Seo, J., Ajmal, M., and Kim, D. (2023, January 4\u20137). Age-of-information aware intelligent MAC for congestion control in NR-V2X. Proceedings of the 2023 Fourteenth International Conference on Ubiquitous and Future Networks (ICUFN), Paris, France.","DOI":"10.1109\/ICUFN57995.2023.10200859"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"2627","DOI":"10.1109\/TITS.2023.3320861","article-title":"NOMA-Assisted Secure Offloading for Vehicular Edge Computing Networks With Asynchronous Deep Reinforcement Learning","volume":"25","author":"Ju","year":"2024","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1470","DOI":"10.1109\/OJCOMS.2023.3291689","article-title":"Multi-Agent DRL Approach for Energy-Efficient Resource Allocation in URLLC-Enabled Grant-Free NOMA Systems","volume":"4","author":"Tran","year":"2023","journal-title":"IEEE Open J. Commun. Soc."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Long, D., Wu, Q., Fan, Q., Fan, P., Li, Z., and Fan, J. (2023). A power allocation scheme for MIMO-NOMA and D2D vehicular edge computing based on decentralized DRL. Sensors, 23.","DOI":"10.3390\/s23073449"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"121526","DOI":"10.1109\/ACCESS.2020.3007115","article-title":"Comparison of IEEE 802.11 p and LTE-V2X: An evaluation with periodic and aperiodic messages of constant and variable size","volume":"8","author":"Gozalvez","year":"2020","journal-title":"IEEE Access"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"89554","DOI":"10.1109\/ACCESS.2021.3090855","article-title":"3GPP NR V2X Mode 2: Overview, Models and System-Level Evaluation","volume":"9","author":"Ali","year":"2021","journal-title":"IEEE Access"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"134575","DOI":"10.1109\/ACCESS.2023.3336686","article-title":"Adaptive RRI Selection Algorithms for Improved Cooperative Awareness in Decentralized NR-V2X","volume":"11","author":"Dayal","year":"2023","journal-title":"IEEE Access"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1109\/MCOMSTD.001.1800036","article-title":"5G new radio: Unveiling the essentials of the next generation wireless access technology","volume":"3","author":"Lin","year":"2019","journal-title":"IEEE Commun. Stand. Mag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"145648","DOI":"10.1109\/ACCESS.2021.3121151","article-title":"Performance analysis of sidelink 5G-V2X mode 2 through an open-source simulator","volume":"9","author":"Todisco","year":"2021","journal-title":"IEEE Access"},{"key":"ref_35","unstructured":"Kingma, D.P., and Ba, J. (2014). Adam: A method for stochastic optimization. arXiv."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1109\/TGCN.2020.3044557","article-title":"Energy harvesting optimization of uplink-NOMA system for IoT networks based on channel capacity analysis using the water cycle algorithm","volume":"5","author":"Bulut","year":"2020","journal-title":"IEEE Trans. Green Commun. Netw."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Ullah, S.A., Zeb, S., Mahmood, A., Hassan, S.A., and Gidlund, M. (2022, January 4\u20138). Deep RL-assisted Energy Harvesting in CR-NOMA Communications for NextG IoT Networks. Proceedings of the 2022 IEEE Globecom Workshops (GC Wkshps), Rio de Janeiro, Brazil.","DOI":"10.1109\/GCWkshps56602.2022.10008522"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"70169","DOI":"10.1109\/ACCESS.2019.2919489","article-title":"IEEE 802.11 bd & 5G NR V2X: Evolution of radio access technologies for V2X communications","volume":"7","author":"Naik","year":"2019","journal-title":"IEEE Access"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"8639","DOI":"10.1109\/TCOMM.2019.2938963","article-title":"Energy-efficient resource allocation in multicarrier NOMA systems with fairness","volume":"67","author":"Muhammed","year":"2019","journal-title":"IEEE Trans. Commun."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4338\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:09:59Z","timestamp":1760108999000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/13\/4338"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,7,4]]},"references-count":39,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["s24134338"],"URL":"https:\/\/doi.org\/10.3390\/s24134338","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,7,4]]}}}