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Register a new userRecursive Periodicity Shifting for Semi-Persistent Scheduling of Time-Sensitive Communication in 5G
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Added by
Nan Jiang
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Various legacy and emerging industrial control applications create the requirement of periodic and time-sensitive communication (TSC) for 5G/6G networks. State-of-the-art semi-persistent scheduling (SPS) techniques fall short of meeting the requirements of this type of critical traffic due to periodicity misalignment between assignments and arriving packets that lead to significant waiting delays. To tackle this challenge, we develop a novel recursive periodicity shifting (RPS)-SPS scheme that provides an optimal scheduling policy by recursively aligning the period of assignments until the timing mismatch is minimized. RPS can be realized in 5G wireless networks with minimal modifications to the scheduling framework. Performance evaluation shows the effectiveness of the proposed scheme in terms of minimizing misalignment delay with arbitrary traffic periodicity.
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Decentralized vehicle-to-everything (V2X) networks (i.e., Mode-4 C-V2X and Mode 2a NR-V2X), rely on periodic Basic Safety Messages (BSMs) to disseminate time-sensitive information (e.g., vehicle position) and has the potential to improve on-road safety. For BSM scheduling, decentralized V2X networks utilize sensing-based semi-persistent scheduling (SPS), where vehicles sense radio resources and select suitable resources for BSM transmissions at prespecified periodic intervals termed as Resource Reservation Interval (RRI). In this paper, we show that such a BSM scheduling (with a fixed RRI) suffers from severe under- and over- utilization of radio resources under varying vehicle traffic scenarios; which severely compromises timely dissemination of BSMs, which in turn leads to increased collision risks. To address this, we extend SPS to accommodate an adaptive RRI, termed as SPS++. Specifically, SPS++ allows each vehicle -- (i) to dynamically adjust RRI based on the channel resource availability (by accounting for various vehicle traffic scenarios), and then, (ii) select suitable transmission opportunities for timely BSM transmissions at the chosen RRI. Our experiments based on Mode-4 C-V2X standard implemented using the ns-3 simulator show that SPS++ outperforms SPS by at least $50%$ in terms of improved on-road safety performance, in all considered simulation scenarios.
In 5G and beyond systems, the notion of latency gets a great momentum in wireless connectivity as a metric for serving real-time communications requirements. However, in many applications, research has pointed out that latency could be inefficient to handle applications with data freshness requirements. Recently, the notion of Age of Information (AoI) that can capture the freshness of the data has attracted a lot of attention. In this work, we consider mixed traffic with time-sensitive users; a deadline-constrained user, and an AoI-oriented user. To develop an efficient scheduling policy, we cast a novel optimization problem formulation for minimizing the average AoI while satisfying the timely throughput constraints. The formulated problem is cast as a Constrained Markov Decision Process (CMDP). We relax the constrained problem to an unconstrained Markov Decision Process (MDP) problem by utilizing Lyapunov optimization theory and it can be proved that it is solved per frame by applying backward dynamic programming algorithms with optimality guarantees. Simulation results show that the timely throughput constraints are satisfied while minimizing the average AoI. Also, simulation results show the convergence of the algorithm for different values of the weighted factor and the trade-off between the AoI and the timely throughput.
With the rapid development of railways, especially high-speed railways, there is an increasingly urgent demand for new wireless communication system for railways. Taking the mature 5G technology as an opportunity, 5G-railways (5G-R) have been widely regarded as a solution to meet the diversified demands of railway wireless communications. For the design, deployment and improvement of 5G-R networks, radio communication scenario classification plays an important role, affecting channel modeling and system performance evaluation. In this paper, a standardized radio communication scenario classification, including 18 scenarios, is proposed for 5G-R. This paper analyzes the differences of 5G-R scenarios compared with the traditional cellular networks and GSM-railways, according to 5G-R requirements and the unique physical environment and propagation characteristics. The proposed standardized scenario classification helps deepen the research of 5G-R and promote the development and application of the existing advanced technologies in railways.
We consider a virtualized RAN architecture for 5G networks where the Remote Units are connected to a central unit via a mid-haul. To support high data rates, the midhaul is realized with a Passive Optical Network (PON). In this architecture, the data are stored at the central unit until the scheduler decides to transmit it through the mid-haul to an appropriate remote unit, and then over the air at the same slot. We study an optimal scheduling problem that arises in this context. This problem has two key features. First, multiple cells must be scheduled simultaneously for efficient operation. Second, the interplay between the time-varying wireless interface rates and the fixed capacity PON needs to be handled efficiently. In this paper, we take a comprehensive look at this resource allocation problem by formulating it as a utility-maximization problem. Using combinatorial techniques, we derive useful structural properties of the optimal allocation and utilize these results to design polynomial-time approximation algorithms and a pseudopolynomial-time optimal algorithm. Finally, we numerically compare the performance of the proposed algorithms to heuristics which are natural generalizations of the ubiquitous Proportional Fair algorithm.
Millimeter-wave (mmWave) frequency bands offer a new frontier for next-generation wireless networks, popularly known as 5G, to enable multi-gigabit communication; however, the availability and reliability of mmWave signals are significantly limited due to its unfavorable propagation characteristics. Thus, mmWave networks rely on directional narrow-beam transmissions to overcome severe path-loss. To mitigate the impact of transmission-reception directionality and provide uninterrupted network services, ensuring the availability of mmWave transmission links is important. In this paper, we proposed a new flexible network architecture to provide efficient resource coordination among serving basestations during user mobility. The key idea of this holistic architecture is to exploit the software-defined networking (SDN) technology with mmWave communication to provide a flexible and resilient network architecture. Besides, this paper presents an efficient and seamless uncoordinated network operation to support reliable communication in highly-dynamic environments characterized by high density and mobility of wireless devices. To warrant high-reliability and guard against the potential radio link failure, we introduce a new transmission framework to ensure that there is at least one basestation is connected to the UE at all times. We validate the proposed transmission scheme through simulations.
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