Jul 2026· La Main· pp. 1-10· 0 citations· 44 references
Computer Science
TL;DR
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.
Abstract
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.
The next generation of wireless systems extends ultra-reliable low-latency communications (URLLC) to the realm of massive connections, termed mURLLC. To address the inherent conflict between stringent quality of service (QoS) requirements in URLLC and the problem of severe and highly fluctuating interference behind demands of massive connectivity, effective fast fading (FF) mitigation and resource allocation strategies are crucial. Through in-depth analysis of FF characteristics, this paper derives optimized configurations for two FF mitigation approaches: protection margin reservation and $K$ -repetition. Furthermore, we integrate these FF mitigation strategies into a hierarchical-clustering (HC)-based resource allocation algorithm for configured-grant in mURLLC. This results in a highly practical and efficient algorithm for managing radio resources and interference in mURLLC scenarios. Simulation results demonstrate that our proposed algorithm achieves over 65% reduction in resource consumption without compromising reliability, significantly enhancing network capacity to support demanding mURLLC applications.
Yichen Guo, Lili Xu, Yihang Cheng et al.· IEEE Transactions on Wireles...· 0 citations
The rapid advancements of next-generation vehicular networks require intelligent, low-latency, and efficient resource management to support heterogeneous services. In this work, we propose a Traffic-aware Dynamic Resource Allocation (TADRA) architecture for UAV-assisted vehicular O-RAN to address the challenges of dynamic traffic conditions, infrastructure failures, and stringent quality of service (QoS) requirements. Due to the dynamic mobility and flexible deployment characteristics, UAV Open Radio Units (O-RUs) in the TADRA architecture support the terrestrial infrastructure under overload or failure conditions, dynamically extending coverage, balancing traffic loads, and restoring service to maintain uninterrupted QoS across diverse and heterogeneous traffic demands. Unlike existing static or single-layer solutions, our proposed TADRA integrates RAN Intelligent Controllers (RICs) with a Hierarchical Traffic-Aware Multi-Agent Twin-Delayed (TMT) algorithm to optimize the allocation of computation and radio resources. This joint optimization problem is NP-hard, highly dynamic, and coupled across agents, making TMT a tractable and adaptive alternative. This hierarchical framework performs traffic prioritization at the upper (application) layer and resource allocation at the lower (MAC) layer, facilitating adaptive decision-making under diverse vehicular traffic patterns. Numerical results demonstrate that our solution provides substantial gains over MATD3, MADDPG, and GA, achieving 17% lower latency, 10% higher throughput, 14% lower energy consumption, and 6.5% higher reliability.
Hayla Nahom Abishu, Ahmed Badawy, Amr Mohamed et al.· IEEE Transactions on Network...· 0 citations
The results demonstrate that the proposed PP-SAPF is suitable for real-time deployment in intelligent transportation systems (ITS) and autonomous vehicles where low latency, reliable connectivity, and adaptive resource management is significant.
Irshad Khan, Neetha Papanna Umalakshmi, Somshekhar Durgaiah et al.· Bulletin of Electrical Engin...· 0 citations
Achieving deterministic latency for time-sensitive flows within integrated 5G and Time-Sensitive Networking (TSN) ecosystem requires the active mitigation of stochastic delays inherent in 5G New Radio (NR). While existing research typically relies on pessimistic guard bands or over-provisioned time-domain resources via wired TSN mechanisms, these approaches fail to adaptively reserve NR resources under dynamic channel conditions to suppress Packet Delay Variation (PDV). This work addresses this gap by proposing a joint NR MAC scheduling and Link Adaptation (LA) framework. We introduce Link Adaptive Semi-Persistent Scheduling (LA-SPS), a framework that ensures cycle-synchronous uplink opportunities by dynamically reconfiguring resource budgets and modulation parameters from real-time channel feedback. To manage the combinatorial complexity of joint resource allocation, we employ a Graph Neural Network (GNN) to encode scalable network states and Proximal Policy Optimization (PPO) for stable, real-time decision-making. This modular framework functions as a radio-side control loop designed for seamless coupling with end-to-end Time-Aware Shaper (TAS) scheduler, enabling a fully co-adaptive industrial network.
Syed Tasnimul Islam, José Fontalvo-Hernández· International Conference on...· 0 citations
This paper proposes a hierarchical computation framework that flexibly supports task execution across local vehicles, neighboring vehicles, RSUs, and cloud resources, and designs an efficient task migration and resource scheduling strategy that improves overall system performance under dynamic network conditions.
Link 16 is a frequency-hopping tactical data link that employs four statically assigned Message Packing Structures (MPSs), each imposing a fixed trade-off among throughput, slot efficiency, and anti-jamming protection. Because these assignments are fixed prior to deployment, current Link 16 networks cannot adapt to runtime variations in traffic load, communication range, or interference conditions, often resulting in inefficient slot utilization. This paper proposes a simulation-based dynamic message packing framework that enables runtime MPS selection based on queue occupancy and inter-participant distance while preserving the standard TDMA structure and waveform. To address contested electromagnetic environments, the baseline mechanism is extended with a lightweight interference-aware component that biases MPS selection toward protection-capable structures based on estimated jammer severity, without altering the underlying adaptation triggers. The proposed framework is implemented in a C++ Link 16 simulation environment and evaluated under five operational scenarios, including non-congested and congested traffic, static and dynamic communication ranges, and probabilistic jammer interference. Results show that under non-congested conditions, the mechanism remains throughput-neutral, with the number of transmitted MPSs closely matching the number of delivered messages, while significantly reducing wasted slot capacity and improving the adaptive use of protection features. Under congestion, dynamic MPS selection enables efficient multi-message packing within TDMA slots, resulting in substantial throughput gains and improved slot utilization. Under jammer interference, throughput decreases due to increased packet loss; however, the extended mechanism preserves a higher absolute delivery rate than static packing by systematically increasing the use of redundancy-enabled and combined protection MPSs, reflecting a shift from capacity-oriented to resilience-oriented adaptation under degraded channel conditions. Overall, the proposed framework provides a practical, standards-compliant runtime optimization for Link 16 systems, enabling improved efficiency under light load, enhanced throughput under congestion, and adaptive resilience under interference.
F. Abut, Mehmet Kızıldağ· IEEE Access· 0 citations