configured grant scheduling

This work addresses the challenge that conventional configured grant (CG) scheduling struggles to meet the bounded latency requirements of deterministic communication under variable traffic conditions. To overcome this limitation, the paper proposes a novel CG scheduling mechanism that integrates traffic prediction with robust optimization, explicitly incorporating prediction uncertainty into resource pre-allocation decisions for the first time. The approach dynamically adapts to the heterogeneous latency constraints of mixed traffic types while ensuring bounded end-to-end delays. By jointly optimizing resource allocation under uncertainty, the method significantly improves resource utilization without compromising timing guarantees. Extensive evaluations demonstrate that the proposed scheme maintains superior performance even in highly dynamic and diverse traffic scenarios, thereby substantially enhancing the system’s capability to support deterministic services.

This work addresses the inherent lack of deterministic communication support in native 5G networks, which struggles to meet the stringent bounded latency and high reliability requirements of Time-Sensitive Networking (TSN) in industrial scenarios. The paper proposes a deeply integrated 5G-TSN configuration grant scheduling scheme that achieves, for the first time, cross-domain joint scheduling. By leveraging key characteristics of TSN traffic—such as periodicity, packet size, and arrival timing—the authors design a deterministic resource allocation algorithm. This approach overcomes the capacity and flexibility limitations of existing solutions, significantly enhancing the network’s ability to support heterogeneous TSN flows with diverse periods while simultaneously guaranteeing end-to-end latency bounds and improving resource utilization efficiency.

To address resource reservation conflicts arising from coexisting multi-cycle traffic flows in Time-Triggered Ethernet (TTE), this paper proposes a Hyperperiod-level Flexible Scheduling (HFS) mechanism. HFS introduces the least common multiple (LCM) of all flow periods—the hyperperiod—as the fundamental unit for scheduling compatibility, thereby overcoming the limitations of conventional fixed-cycle scheduling. We theoretically prove that HFS achieves unbounded throughput gain. For the NP-hard joint problem of path planning and time-triggered scheduling, we design an efficient heuristic algorithm, HFS-LLF. Crucially, HFS is fully backward-compatible with existing TTE systems and enables dynamic reconfiguration of paths and resource allocations for individual flows across sub-cycles within a hyperperiod. Experimental evaluation demonstrates that HFS increases the number of admissible flows by up to 6× and that HFS-LLF solves instances 10⁴× faster than a general-purpose integer linear programming (ILP) solver.

Ensuring deterministic uplink performance for time-sensitive traffic in industrial 5G–Time-Sensitive Networking (TSN) convergence under mobility remains challenging. Method: This paper proposes a heterogeneous wireless resource joint-scheduling architecture, pioneering the use of 5G TDD base stations as transparent TSN bridges to enable end-to-end time-aware scheduling. It integrates static configuration with dynamic scheduling (Proportional Fair/Max C/I), jointly modeling bridging latency, time-aware traffic shaping, and flow filtering & policing to guarantee deadline compliance for periodic flows. Contribution/Results: Experiments demonstrate a 28% improvement in radio resource efficiency over Configured Grant baseline; 100% of time-sensitive flows meet their deadlines; and non-deterministic traffic throughput increases significantly. The work establishes, for the first time, the feasibility of deploying 5G infrastructure as transparent TSN bridges and delivers a verifiable, deterministic uplink scheduling framework for industrial 5G–TSN integration.

To address the challenge of deterministic low-latency scheduling for periodic message transmission between antennas and remote processing units in Cloud-RAN—where strict protocol deadlines must be met while avoiding buffering and collision delays induced by statistical multiplexing—this paper pioneers the application of deterministic conflict-free scheduling to Cloud-RAN fronthaul networks. We propose two algorithms: (i) an analytical zero-buffer scheduling algorithm tailored for short-path or light-load scenarios, and (ii) PMLS (Periodic Message Latency Scheduling), a heuristic algorithm supporting bounded buffering. We theoretically prove that a zero-buffer feasible schedule always exists under short-path or low-load conditions. Experimental results demonstrate that PMLS achieves zero-delay deterministic schedules with high probability even under full load, significantly enhancing latency predictability and resource utilization.

This study addresses the challenge of excessive uplink latency in existing 5G dynamic scheduling—caused by signaling overhead—which hinders support for ultra-reliable low-latency communication (URLLC) requirements in Industry 4.0. The authors present the first implementation and validation of the 5G NR Configured Grant (CG) mechanism within the open-source system-level simulator ns-3 5G-LENA. By pre-allocating uplink resources, CG eliminates per-packet scheduling requests, while enhanced OFDMA modeling improves the fidelity of 5G NR’s flexibility. This work fills a critical gap in open-source platforms for simulating URLLC-enabling features and provides a reproducible framework for scheduling research. Simulation results align closely with theoretical analysis, demonstrating that CG significantly reduces latency, meets industrial reliability demands, and underscores the importance of efficient radio resource utilization.

This study addresses the lack of empirical evaluation of NVIDIA ConnectX NICs’ high-precision scheduling and hardware timestamping capabilities under real-world conditions, which has hindered clear assessment of their suitability for stringent timing requirements in deterministic networks such as 5G fronthaul and Time-Sensitive Networking (TSN). Leveraging an FPGA-based nanosecond-precision measurement platform, this work presents the first public quantification of the hardware timestamp accuracy and Accurate Scheduling transmission timing performance of the ConnectX-7 NIC. Experimental results show that cross-device timestamp deviations are approximately ±7–8 ns, and 99% of scheduled frames are transmitted within ±900 ns of their target time, with rare outliers reaching up to 5 μs. These findings indicate that the NIC meets the tens-of-microseconds timing demands of 5G fronthaul but falls short of the sub-microsecond precision required by TSN, thereby filling a critical gap in industrial empirical understanding of this hardware’s deterministic networking capabilities.

Existing datacenter transport protocols couple rate control with packet scheduling, causing steady-state queues to accumulate as flow count increases and degrading latency performance. This work proposes Clocked ACK-Paced Synchronization (CAPS), which decouples rate control from scheduling and precisely regulates the timing of packet arrivals at the bottleneck link under a given stable rate, thereby reframing queuing as a timing alignment problem. CAPS introduces an ACK-clock-based phase-locking mechanism that employs a lightweight distributed scheduling layer to compensate for heterogeneous round-trip times (RTTs) and partitions bottleneck time into slots aligned with the ACK clock to enable inter-flow phase correction. Experimental results demonstrate that CAPS reduces worst-case queue occupancy by 5–10× across diverse topologies and traffic patterns while sustaining full throughput.

研究通过结合MaxWeight算法和UCB估计，解决了用户关联、调度与速率自适应跨时间尺度联合设计问题，以最大化网络吞吐量并确保用户间公平性。

This study addresses the stringent timing requirements of 5G fronthaul and Time-Sensitive Networking (TSN) by presenting the first quantitative evaluation of hardware timestamping and scheduled transmission performance on the Intel E830 network interface card. A deterministic frame generation and nanosecond-level measurement system is developed on an FPGA platform, integrated with a clock drift compensation algorithm for empirical analysis. Experimental results demonstrate that the E830 achieves timestamp jitter of merely a few nanoseconds, with 99% of inter-frame interval deviations remaining below 300 ns. These findings establish that while the E830 is well-suited for microsecond-level applications, it falls short of satisfying TSN nanosecond-level standards, thereby delineating critical applicability boundaries for its deployment in time-sensitive networks.