[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-38844-en":3,"doc-seo-38844-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},38844,1099513958607,"Jiven","https://ap-avatar.wpscdn.com/avatar/100002390cf8733938c?x-image-process=image/resize,m_fixed,w_180,h_180&k=1778829742770036399",8,"Research & Report","Optimizing Hybrid RIS-Aided ISAC Systems in V2X Networks","Vehicle-to-everything (V2X) networks require physical layer security to protect confidential information from eavesdroppers while simultaneously supporting radar sensing. This paper studies a hybrid active-passive RIS-enhanced integrated sensing and communication (ISAC) system where V2V links reuse the spectrum occupied by V2I links. It jointly optimizes RSU transmit beamforming, V2X spectrum reuse, and hybrid RIS reflection beamforming to maximize V2I sum secrecy rate while maintaining V2V communication quality and RSU target sensing capability. A hierarchical twin delayed deep deterministic policy gradient method is developed to learn secure beamforming and sharing strategies in a dynamic nonconvex model against eavesdropping.","Optimizing Hybrid RIS-Aided ISAC Systems in V2X Networks: A Deep Reinforcement Learning Method for Anti-Eavesdropping Techniques  \nYu Yao , Member, IEEE, Zhixing Zhu, Pu Miao, Member, IEEE, Xu Cheng, Senior Member, IEEE, Feng Shu , Member, IEEE, and Jiangzhou Wang, Fellow, IEEE  \nAbstract—Physical layer security (PLS) technique is expected to play a crucial part in the vehicle-to-everything (V2X) networks, by offering secure transmission to protect confidential information from potential eavesdropper. Considering a hybrid active-passive reconfigurable intelligent surfaces (RISs)-enhanced integrated sensing and communication (ISAC) system, this paper proposes a novel secure scheme for transmitting confidential information and performing radar sensing, where vehicle-to-vehicle (V2V)links share the spectrum resource preoccupied by vehicle-toinfrastructure (V2I) links. We aim to optimize the sum secrecy rate of V2I links by jointly designing the transmit beamforming of RSU, the radio spectrum reuse scheme of V2X links, and active and passive reflection beamforming of hybrid RIS. With above optimization, the proposed approach can enhance secure communication performance of V2I links while guaranteeing the communication quality of V2V links and target sensing capacity of RSU. Since the system model is dynamic, and it is difficult to handle the nonconvex problem, an efficient hierarchical twin delayed deep deterministic policy gradient (HTD3) method is developed to learn the secure beamforming and spectrum sharing strategies against potential eavesdropping. The proposed method decomposes the spectrum allocation into the deep Q-network procedure and designs the secure beamforming variables by employing the TD3 algorithm. Numerical results exhibit that given a sufficient power budget of hybrid RIS, our HTD3-based method enhances both the secure  \nReceived 29 June 2024; revised 28 October 2024; accepted 13 January 2025 . Date of publication 6 February 2025; date of current version 20 June 2025 . This work was supported in part by the National Natural Science Foundation of China under Grant U22A2002, Grant 62261021, and Grant 62071234, in part by the Hainan Province Science and Technology Special Fund under Grant ZDYF2024GXJS292, in part by the Scientific Research Fund Project of Hainan University under Grant KYQD(ZR)-21008, in part by the Collaborative Innovation Center of Information Technology, Hainan University under Grant XTCX2022XXC07, and in part by the National Key Research and Development Program of China under Grant 2023YFF0612900 . The review of this article was coordinated by Dr. Muhammad Ismail. (Corresponding author: Yu Yao.)  \nYu Yao is with the School of Information and Communication Engineering, Hainan University, Haikou 570288, China (e-mail: [yaoyu@hainanu.edu.cn](yaoyu@hainanu.edu.cn)).  \nZhixing Zhu is with the School of Information Engineering, East China Jiaotong University, Nanchang 330013, China (e-mail: [zxingchuh@ecjtu.edu.cn](zxingchuh@ecjtu.edu.cn)).  \nPu Miao is with the School of Electronic and Information Engineering, Qingdao University, Qingdao 266071, China ([e-mail: mpvae@qdu.edu.cn](e-mail: mpvae@qdu.edu.cn)).  \nXu Cheng is with the School of Electronics and Communication Engineering, Sun Yat-sen University, Shenzhen 510275, China (e-mail: [chengx95@mail.sysu.edu.cn](chengx95@mail.sysu.edu.cn)).  \nFeng Shu is with the School of Information and Communication Engineering, Hainan University, Haikou 570228, China, and also with the School of Electronic and Optical Engineering, Nanjing University of Science and Technology, Nanjing 210094, China (e-mail: [shufeng0101@163.com](shufeng0101@163.com)).  \nJiangzhou Wang is with the School of Engineering, University of Kent, CT2 7NT Canterbury, U.K. (e-mail: [j.z.wang@kent.ac.uk](j.z.wang@kent.ac.uk)).  \nDigital Object Identifier 10.1109/TVT.2025.3538471  \ncommunication performance of V2I links and radar detection capability of RSU compared with the existing learning metho","cbCainUJ4geSWycX","https://ap.wps.com/l/cbCainUJ4geSWycX","pdf",1678139,1,16,"English","en",105,"# Introduction\n## Motivation and problem statement\n## Physical layer security for ISAC in V2X\n## Threat model: eavesdropping during sensing/communication","[{\"question\":\"What security goal does the paper target in V2X integrated sensing and communication?\",\"answer\":\"The work targets anti-eavesdropping physical-layer security for transmitting confidential information while radar sensing is performed within the ISAC framework.\"},{\"question\":\"How does the system enable coexistence of V2V and V2I transmissions?\",\"answer\":\"V2V links share and reuse the spectrum resource that is occupied by V2I links, with the spectrum allocation optimized jointly with beamforming and RIS reflection settings.\"},{\"question\":\"Why is the proposed learning method needed instead of direct optimization?\",\"answer\":\"The dynamic system leads to a nonconvex optimization problem, so the paper develops a hierarchical twin delayed deep deterministic policy gradient (HTD3) approach to learn secure beamforming and spectrum sharing strategies efficiently.\"}]",1783073921,40,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"optimizing-hybrid-ris-aided-isac-systems-in-v2x-networks","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/optimizing-hybrid-ris-aided-isac-systems-in-v2x-networks/38844/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"What security goal does the paper target in V2X integrated sensing and communication?","Question",{"text":74,"@type":75},"The work targets anti-eavesdropping physical-layer security for transmitting confidential information while radar sensing is performed within the ISAC framework.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"How does the system enable coexistence of V2V and V2I transmissions?",{"text":79,"@type":75},"V2V links share and reuse the spectrum resource that is occupied by V2I links, with the spectrum allocation optimized jointly with beamforming and RIS reflection settings.",{"name":81,"@type":72,"acceptedAnswer":82},"Why is the proposed learning method needed instead of direct optimization?",{"text":83,"@type":75},"The dynamic system leads to a nonconvex optimization problem, so the paper develops a hierarchical twin delayed deep deterministic policy gradient (HTD3) approach to learn secure beamforming and spectrum sharing strategies 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