[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83043-en":3,"doc-seo-83043-105":29,"detail-sidebar-cat-0-en-105":91},{"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":20,"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},83043,13056703019404,"Miles","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Repeated Contention Scheduling: A Novel Resource Allocation Algorithm Toward 6G Vehicular Networks","Efficient decentralized resource allocation is a core challenge in NR-V2X sidelink communications, where Semi-Persistent Scheduling (SPS) and Dynamic Scheduling (DS) can generate persistent collisions and limited adaptability under dynamic, dense traffic. The work introduces Repeated Contention Scheduling (RCS), a fully distributed algorithm based on multi-round, feedback-driven contention that removes long-term reservations. Simulations show gains in success probability, reduced collision/loss, and improved timeliness metrics such as Packet Inter-Reception Delay and Age of Information, especially under high load. An SDR-based testbed confirms robustness with realistic hardware impairments and matches theory and simulations.","arXiv :2607 .06 103v 1 [ cs .NI ] 7 Jul 2026  \n\n| © 2026 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |\n| --- |\n| 2026 Mediterranean Artificial Intelligence and Networking Conference (MAIN 2026) |\n\nRepeated Contention Scheduling: A Novel Resource Allocation Algorithm Toward 6G Vehicular Networks  \nAlexey Rolich∗ , Marco Tricco∗ , Simone Paroli∗ , Mert Yildiz∗ , and Andrea Baiocchi∗  \n∗ University of Rome Sapienza, Italy  \n{alexey.rolich, mert.yildiz, [andrea.baiocchi}@uniroma1.it](andrea.baiocchi}@uniroma1.it)[ ](andrea.baiocchi}@uniroma1.it){paroli.1853547, [tricco.1894220}@studenti.uniroma1.it](tricco.1894220}@studenti.uniroma1.it)  \nAbstract—Efficient decentralized resource allocation remains a fundamental challenge in NR-V2X sidelink communications, where conventional Semi-Persistent Scheduling (SPS) and Dynamic Scheduling (DS) suffer from persistent collisions and limited adaptability under dynamic and dense conditions. This paper proposes Repeated Contention Scheduling (RCS), a novel resource allocation algorithm based on multi-round, feedbackdriven contention that eliminates long-term reservations and enables fully distributed operation. Simulations demonstrate that RCS outperforms SPS and DS in terms of success probability, collision and loss reduction, and timeliness metrics such as Packet Inter-Reception Delay and Age of Information, particularly under high load. The practical feasibility of the approach is validated through an SDR-based experimental testbed, which confirms robust operation under realistic hardware impairments and closely matches theoretical and simulation results. These findings establish RCS as a viable and scalable solution for resource allocation in 5G NR sidelink and a promising candidate for future 6G vehicular communication systems.  \nIndex Terms—5G, 6G, V2X, Semi-Persistent Scheduling, Sidelink, Age of Information, Dynamic Scheduling, Persistence, Vehicular Networks, Repeated Contention, Vehicular Communication, Resource Allocation.  \nI. INTRODUCTION  \nIntelligent Transportation Systems (ITS) constitute a key component of next-generation transportation systems, enabling improved safety, traffic efficiency, and automation through pervasive connectivity. Vehicular networks provide the communication backbone of ITS, supporting real-time information exchange among vehicles, infrastructure, and vulnerable road users. In this context, 5G New Radio (NR) -Vehicle-to-Everything (V2X) has emerged as a technological solution offering high-reliability, low-latency communication tailored to advanced vehicular applications [1] . A central feature of NR-V2X is sidelink communication, which enables direct and decentralized interactions in both in-coverage (Mode 1) and out-of-coverage (Mode 2) scenarios [1, 2] .  \nEfficient sidelink resource allocation remains a fundamental challenge in dynamic vehicular environments characterized by high mobility, heterogeneous traffic density, and rapidly varying channel conditions. The 5G NR-V2X sidelink framework defines two operational modes. In Mode 1, the gNB performs centralized scheduling through dynamic grants for per-transmission allocation and configured grants for semipersistent reservations, supporting both periodic and aperiodic traffic under network coverage. In Mode 2, user equipments autonomously select resources based on sensing mechanisms.  \nTwo standardized allocation schemes are defined for this mode: Semi-Persistent Scheduling (SPS) and Dynamic Scheduling (DS) [3, 4] .  \nSPS adopts a reservation-based strategy in which resources are selected and retained over multiple transmission intervals  \naccording to a predefined Resource ","cbCailc2U9Ob4F4Z","https://ap.wps.com/l/cbCailc2U9Ob4F4Z","pdf",538189,1,11,"English","en",105,"# Introduction\n## NR-V2X sidelink modes and allocation schemes\n## Limitations of SPS and DS\n## Related work and mitigation approaches","[{\"question\":\"What problem does the paper address in NR-V2X sidelink communications?\",\"answer\":\"It addresses the difficulty of efficient decentralized resource allocation, where SPS and DS can lead to persistent collisions and insufficient adaptability in dynamic, dense vehicular scenarios.\"},{\"question\":\"How does Repeated Contention Scheduling (RCS) differ from SPS and DS?\",\"answer\":\"RCS uses multi-round, feedback-driven contention to eliminate long-term reservations and enable fully distributed operation, rather than relying on persistent reservation reuse (SPS) or per-packet independent selection (DS).\"},{\"question\":\"What evidence supports the effectiveness and feasibility of RCS?\",\"answer\":\"Simulations show higher success probability and lower collision/loss with better timeliness metrics under high load, and an SDR-based experimental testbed validates robust operation under realistic hardware impairments closely matching theoretical and simulation 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problem does the paper address in NR-V2X sidelink communications?","Question",{"text":75,"@type":76},"It addresses the difficulty of efficient decentralized resource allocation, where SPS and DS can lead to persistent collisions and insufficient adaptability in dynamic, dense vehicular scenarios.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How does Repeated Contention Scheduling (RCS) differ from SPS and DS?",{"text":80,"@type":76},"RCS uses multi-round, feedback-driven contention to eliminate long-term reservations and enable fully distributed operation, rather than relying on persistent reservation reuse (SPS) or per-packet independent selection (DS).",{"name":82,"@type":73,"acceptedAnswer":83},"What evidence supports the effectiveness and feasibility of RCS?",{"text":84,"@type":76},"Simulations show higher success probability and lower collision/loss with better timeliness metrics under high load, and an SDR-based experimental testbed validates robust operation under 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