Sensing-based Semi-persistent Scheduling Research Articles

The Shared Experience Actor–Critic (SEAC) Approach for Allocating Radio Resources and Mitigating Resource Collisions in 5G-NR-V2X Mode 2 Under Aperiodic Traffic Conditions

5G New Radio (NR)-V2X, standardized by 3GPP Release 16, includes a distributed resource allocation Mode, known as Mode 2, that allows vehicles to autonomously select transmission resources using either sensing-based semi-persistent scheduling (SB-SPS) or dynamic scheduling (DS). In unmanaged 5G-NR-V2X scenarios, SB-SPS loses effectiveness with aperiodic and variable data. DS, while better for aperiodic traffic, faces challenges due to random selection, particularly in high traffic density scenarios, leading to increased collisions. To address these limitations, this study models the Cellular V2X network as a decentralized multi-agent networked Markov decision process (MDP), where each vehicle agent uses the Shared Experience Actor–Critic (SEAC) technique to optimize performance. The superiority of SEAC over SB-SPS and DS is demonstrated through simulations, showing that the SEAC with an N-step approach achieves an average improvement of approximately 18–20% in enhancing reliability, reducing collisions, and improving resource utilization under high vehicular density scenarios with aperiodic traffic patterns.

Reuse Distance-Aided Resource Selection Mechanisms for NR-V2X Sidelink Communication.

Cellular vehicle-to-everything (C-V2X) facilitates direct communication between vehicles and other user equipment (UE) to improve the efficiency of the Internet of vehicles communication through sidelink. In addition, in the new radio vehicle-to-everything (NR-V2X) Mode 2, users can automatically select resources using the conventional sensing-based semi-persistent scheduling (SB-SPS) resource selection algorithm. This mechanism allows users to generate a list of available resources after a sensing window, after which the users can randomly select resources, and the resource can be used continuously over multiple periods before reselection. However, during the sensing window, neighbors may generate a similar list of available resources, and random selection may lead to resource conflicts. This phenomenon may lead to deteriorated communication performance and increased latency due to incorrect reception. Therefore, this paper proposes a reuse distance-aided resource selection (RD-RS) method which integrates resource reuse distance judgement with SB-SPS to mitigate resource conflicts and interference caused by random selection. Moreover, the reuse distance judgement is performed before the final resource selection, and whether the user will select the current resource depends on the reuse distance between that user and other occupiers. Furthermore, the performance of the proposed scheme is compared with other algorithms. Simulation results show that the proposed RD-RS not only achieves a higher packet reception ratio (PRR) but also effectively reduces the inter-packet gap (IPG). Moreover, in specific scenarios, the proposed method outperforms conventional schemes by 9% in terms of PRR and 70% in terms of Range.

Dynamic Spectrum Access for C-V2X via Imitating Indian Buffet Process

In dense traffic cases, the channels among vehicles and infrastructures in cellular vehicle-to-everything (C-V2X) network are likely to be congested. Vehicles can select spectrum resources autonomously by adopting sensing-based semipersistent scheduling scheme, which may result in frequent packet collisions due to the random selection process, especially when spectrum resources are limited. So far, there still lacks a definite stochastic expression to characterize the channel selection process for vehicles in C-V2X. In this paper, we propose a novel deep reinforcement learning (DRL) based dynamic spectrum access (DSA) algorithm for C-V2X via imitating Indian buffet process (IBP), aiming to meet the vehicles’ strict communication requirements on high transmission rate and low collision probability. First, we explore the correlations among historical spectrum access data to acquire the channel availability list. Then, we exploit DRL to achieve distributive DSA among vehicles. Specifically, the channel state prediction for the distributive DSA is facilitated via imitating the classic IBP, and the spectrum access decisions are made by leveraging the deep Q-learning network combined with long short-term memory technique. Finally, comprehensive simulation results are presented to show that the proposed algorithm can improve the transmission rate by 15% and reduce the collision probability by 12% with a false alarm probability of 0.1 compared with other spectrum access methods.

Performance Analysis of Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC Protocol for C-V2X

Sensing-based Semi-Persistent Scheduling (SB-SPS) MAC protocol is proposed as part of the latest cellular vehicle to everything (C-V2X) standard for medium access between vehicles. As C-V2X uses LTE based frame structure, mode 4 of the C-V2X standard uses SB-SPS to allocate resource blocks effectively. C-V2X shows great potential for the future as it brings many improvements such as enhanced range, reliability, and the ability to support and evolve with emerging technologies such as 5G. In this article, the SB-SPS protocol’s performance was analyzed in different scenarios using OMNET++, SUMO, and Veins simulator. Different vehicle speeds and densities were used to observe the effect on packet loss and throughput. It was found that as packet loss decreased, throughput increased when the mobility of vehicles decreased. The effects of changing some important parameters of SB-SPS were also observed. The results showed that while parameters such as increasing the number of subchannels increased the packet delivery ratio (PDR), the change in the probability of resource reselection parameter did not affect the PDR.

On the Impact of Multiple Access Interference in LTE-V2X and NR-V2X Sidelink Communications

Developing radio access technologies that enable reliable and low-latency vehicular communications have become of the utmost importance with the rise of interest in autonomous vehicles. The Third Generation Partnership Project (3GPP) has developed Vehicle to Everything (V2X) specifications based on the 5G New Radio Air Interface (NR-V2X) to support connected and automated driving use cases, with strict requirements to fulfill the constantly evolving vehicular applications, communication, and service demands of connected vehicles, such as ultra-low latency and ultra-high reliability. This paper presents an analytical model for evaluating the performance of NR-V2X communications, with particular reference to the sensing-based semi-persistent scheduling operation defined in the NR-V2X Mode 2, in comparison with legacy sidelink V2X over LTE, specified as LTE-V2X Mode 4. We consider a vehicle platooning scenario and evaluate the impact of multiple access interference on the packet success probability, by varying the available resources, the number of interfering vehicles, and their relative positions. The average packet success probability is determined analytically for LTE-V2X and NR-V2X, taking into account the different physical layer specifications, and the Moment Matching Approximation (MMA) is used to approximate the statistics of the signal-to-interference-plus-noise ratio (SINR) under the assumption of a Nakagami-lognormal composite channel model. The analytical approximation is validated against extensive Matlab simulations that a show good accuracy. The results confirm a boost in performance with NR-V2X against LTE-V2X, particularly for high inter-vehicle distance and a large number of vehicles, providing a concise yet accurate modeling rationale for planning and adaptation of the configuration and parameter setup of vehicle platoons, without having to resort to extensive computer simulation or experimental measurements.

Performance Analysis and Optimization for Semi-Persistent Scheduling in C-V2X

For periodical beacon broadcasting in cellular vehicle-to-everything (C-V2X) networks, a distributed reservation media access control (MAC) protocol, the sensing-based semi-persistent scheduling (SPS), is adopted. However, how to quantify the communication reliability and latency is an open issue, which is critical for low-latency and high-reliability services. In this paper, an analytical model for SPS is presented, based on which the impacts of beacon rate, range settings and system configuration on access collision probability and delay outage probability are quantified. The analytical model provides important insights and guideline to adapt and optimize protocol parameters including the sensing range, transmit power and resource reservation. The enhanced MAC protocol can maintain high-reliability and low-latency services with a wide range of vehicle density. Simulations are conducted to validate the analysis and the results demonstrate that the proposed MAC enhancement solution can reduce collision probability while ensuring the delay outage probability based on service requirements.

Congestion Control in Autonomous Resource Selection of Cellular-V2X

Intelligent transportation systems have recently become a promising technology for future industry to provide safe, green, and automated driving. In this regard, the Third Generation Partnership Project (3GPP) has proposed to utilize cellular communication to enable direct communication between vehicles with and without cellular infrastructure assistance. 3GPP has introduced the Sensing-Based Semi-Persistent Scheduling (S-SPS) technique when coverage of the cellular system is absent. S-SPS faces resource collision and performance degradation problems when channel load increases in the network. This paper suggests a decentralized congestion control and transmission power control mechanism (TPC-DCC) with an adaptive threshold for the received signal as a combination method to decrease channel load in the network. Furthermore, this work introduces a novel channel load adjustment. The new adjusting algorithm is based on a constant difference between the upper and lower boundaries of channel load at each level to handle channel overload and provide more flexibility using DCC mechanisms. The interactions of the proposed algorithm with S-SPS and the Extended-Estimation Reservation Resource Allocation (E-ERRA) algorithms that the authors previously proposed are investigated. The results indicate that system performance can be substantially improved when the transmission power and reception threshold are adaptively adjusted to the proposed channel load adjustment. The results of E-ERRA with the proposed channel load adjustment method show promising results compared to S-SPS.

Performance of Fuzzy Inference System for Adaptive Resource Allocation in C-V2X Networks

Mode 4 of 3GPP Cellular Vehicle-to-Everything (C-V2X) uses a new Sensing-Based Semi-Persistent Scheduling (SB-SPS) algorithm to manage its radio resources. SB-SPS applies a probabilistic approach to provide the resource allocation in the system. The resource keep probability (Prk) variable plays an essential role in the resource allocation mechanism. Most of the previous works used a fixed Prk value. However, the Packet Delivery Ratio (PDR) can be improved by adapting the optimal Prk value. Hence, we propose a Fuzzy Inference System (FIS) with two inputs, distance, and Channel State Information (CSI) to determine the suitable Prk. The simulation results show that the proposed FIS method outperforms the other methods for sparse and congested road scenarios, with total numbers of vehicles at 200 and 400, respectively.

Multiagent Reinforcement Learning-Based Semi-Persistent Scheduling Scheme in C-V2X Mode 4

The Third Generation Partnership Project has standardized cellular vehicle-to-everything (C-V2X) sidelink Mode 4 to support direct communication between vehicles. In Mode 4, the sensing-based semipersistent scheduling (SPS) scheme enables vehicles to autonomously reserve and select radio resources. In particular, SPS has three processes to realize the resource scheduling, including continuously sensing resources, probabilistically reselecting resources, and periodically reserving resources. However, vehicles randomly select resources from the available resource lists in the resource reselection process, resulting in frequent packet collisions especially when radio resources are insufficient. Unlike the traditional SPS, this paper proposes a multiagent deep reinforcement learning-based SPS (RL-SPS) algorithm to help vehicles select appropriate radio resources with the aim of reducing packet collisions. Furthermore, a multi-head attention mechanism is adopted to improve the training efficiency by helping vehicles selectively pay attention to the observations and actions of neighbouring vehicles. It is worth noting that the RL-SPS algorithm fits the characteristics of Mode 4, which selects resources without requiring any global information. Simulation results show that RL-SPS outperforms other decentralized approaches and demonstrate the scalability and robustness of RL-SPS in a dynamic vehicular network.

Mathematical Representation for Reliability of Sensing-Based Semi-Persistent Scheduling in LTE-V2X

Since 3GPP has introduced sensing-based semi-persistent scheduling (SPS) into the MAC layer of LTE-V2X Mode 4 in release 14, various studies have been carried out to evaluate its performance. However, until now, there is still no clear mathematical expression for the reliability of this scheduling. To this end, we try to provide a theoretical representation of the scheduling reliability. Firstly, we present a description of the physical layer and MAC layer of sensing-based SPS, and then we abstract the scheduling mathematically and give the definition of the scheduling reliability and channel busy rate. Secondly, according to the characteristics of semi-persistent of scheduling, we formulate the reliability equation through the principle of iteration, thereby obtaining the closed-form expression of the scheduling reliability. Finally, we compare the theoretical representation of reliability with system simulations, and results show that the theoretical curve can represent the reliability of scheduling excellently.

Full-Duplex Multiple Access Mechanism for Connected Vehicles Operating at Different Autonomous Levels in NR eV2X VANETs

Future connected and autonomous vehicles (CAVs) will operate at different autonomous levels for decades. Therefore, we propose a novel prioritisation scheme according to the autonomous levels of CAVs, and a corresponding multiple access mechanism, to be named full-duplex prioritised scheduling (FDPS) protocol, to enhance the delivery of high-priority packets in future New Radio (NR) enhanced vehicle-to-everything communication (eV2X) vehicular ad hoc networks (VANETs). Comparing to the standardised sensing-based semi-persistent scheduling (SB-SPS) protocol, this paper presents how collision detection is enabled during the broadcast, how collisions are resolved, how the priority of a packet from a colliding CAV is recognised, and how the broadcast of high-priority packets is enhanced. Both protocols are evaluated through mathematical formulations and simulations in terms of average successful packet delivery rate (PDR), collision duration, and latency. Simulation results have firstly validated the mathematical analysis, they have also shown the enhancement of packets delivery in future NR eV2X VANETs when the self-interference suppression (SIS) factor is better than 16%, which is achievable by deploying the existing SIS technologies.

Dynamic resource scheduling for real-time group broadcasting in 6G cellular vehicular networks

Vehicle-to-Vehicle (V2V) messaging is an indispensable component of connected autonomous vehicle systems. The 3rd Generation Partnership Project (3GPP) is designed to support V2V communication without any infrastructure using sensing-based Semi-Persistent Scheduling (SPS) in order to avoid resource collisions for Cooperative Awareness Messages (CAMs) transmission. However, the legacy system suffers from significant collisions in a traffic congestion environment and resource waste in light traffic conditions. To address these problems, in this paper we propose a novel dynamic resource scheduling algorithm for real-time group broadcasting, inspired by the Lyapunov optimization framework, where the optimization objective is to minimize time-average failure probability subject to queue stability. Through extensive simulations, we show that the proposed scheduling algorithm outperforms the standard in both traffic jams and leisurely road environments.

Adaptive sensing-based semipersistent scheduling with channel-state-information-aided reselection probability for LTE-V2V

LTE-V2V mode 4 utilizes sensing-based semipersistent scheduling (SB-SPS) to support the vehicle user equipment to autonomously select appropriate radio resources and allow the UE to be retained for several consecutive periods. Then, resource reselect is determined based on the reselection probability P k . For conventional SB-SPS, the value of P k is fixed identically for all vehicles. In this work, we introduce an improved SB-SPS scheme, which aims to adaptively adjust the value of the reselection probability P k based on the channel state information. Through simulations, we concluded that the proposed algorithm outperformed the conventional algorithm and effectively improve the performance of each scenario.

Space Division Multiple Access for Cellular V2X Communications

Vehicular communication is the backbone of future Intelligent Transportation Systems (ITS). It offers a network-based solution for vehicle safety, cooperative awareness, and traffic management applications. For safety applications, Basic Safety Messages (BSM) containing mobility information is shared by the vehicles in their neighborhood to continuously monitor other nearby vehicles and prepare a local traffic map. BSMs are shared using mode 4 of Cellular V2X (C-V2X) communications in which resources are allocated in an ad hoc manner. However, the strict packet transmission requirements of BSM and hidden node problem causes packet collisions in a vehicular network, thus reducing the reliability of safety applications. Moreover, as vehicles choose the transmission resources in a distributed manner in mode 4 of C-V2X, the packet collision problem is further aggravated. This paper presents a novel solution in the form of a Space Division Multiple Access (SDMA) protocol that intelligently schedules BSM transmissions using vehicle position data to reduce concurrent transmissions from hidden node interferers. The proposed protocol works by dividing road segments into clusters and sub-clusters. Several sub-frames are allocated to a cluster and these sub-frames are reused after a certain distance. Within a cluster, sub-channels are allocated to sub-clusters. We implement the proposed SDMA protocol and evaluate its performance in a highway vehicular network. Simulation results show that the proposed SDMA protocol outperforms standard Sensing-Based Semi Persistent Scheduling (SB-SPS) in terms of safety range and packet delay.

Resolving Persistent Packet Collisions through Broadcast Feedback in Cellular V2X Communication

The Third Generation Partnership Project (3GPP) Release 16 defines the sensing-based semi-persistent scheduling (SPS) as the resource allocation scheme for Sidelink Mode 2 in New Radio (NR)-based vehicle-to-everything (V2X) communication. A well-known issue in Mode 2 is the persistent packet collision that results from two or more vehicles repeatedly using the same resource for transmission. It may create serious safety problems when the vehicles are in a situation where only the broadcast safety beacons can assist in driving. To resolve this issue, a solution that relies on the feedback from neighboring vehicles is proposed, through which the vehicles suffering from persistent packet collisions can quickly part and select other resources. Extensive simulations show that the proposed broadcast feedback scheme reduces persistent packet collisions by an order of magnitude compared to SPS, and it is achieved without sacrificing the average packet reception ratio (PRR). Namely, it is the quality aspect (i.e., burstiness) of the packet collisions that the proposed scheme addresses rather than the quantity (i.e., total number of collision losses). By preventing extended packet loss events, the proposed scheme is expected to serve NR V2X better, which requires stringent QoS in terms of the information update delay thereby helping to reduce the chances of vehicle crashes.

An Evasive Scheduling Enhancement Against Packet Dropping Attacks in C-V2X Communication

Third Generation Partnership Project (3GPP) has standardized the Sensing-Based Semi-Persistent Scheduling (SB-SPS) as the radio resource allocation algorithm for Cellular V2X (C-V2X) sidelink communication Mode 4. The algorithm leverages on past resource use pattern and reservation information of neighbor vehicles to reduce the chances of packet collisions. However, the very predictability can be exploited by potential attackers to intentionally cause packet collisions in the predicted transmission locations in the resource plane. In this letter, we demonstrate that such packet dropping attack can cause the victim to become a “ghost vehicle” to neighbors for a long duration. If used in highly safety-critical situations, the attack can push the victim into a situation of higher crash risk, which would be worse off than not having the C-V2X safety communication. Therefore, we propose an enhancement to the SB-SPS algorithm to guard against the attack by randomizing actually used resource locations to a certain degree. We demonstrate the effectiveness of the proposed enhancement through analysis and simulation, and discuss its cost aspect as well.

On Reliability Bound and Improvement of Sensing-Based Semipersistent Scheduling in LTE-V2X

After the sensing-based semipersistent scheduling (SPS) is introduced in the media access control layer of the long-term evolution vehicle-to-everything (LTE-V2X) Mode 4, many tests have been conducted to measure its performance. However, until now, there is still no clear mathematical expression for the reliability of this scheduling. To this end, in this article, we attempt to provide the lower and upper bounds of the reliability and propose a distributed algorithm for improving reliability. First, we give a mathematical description of sensing-based SPS and apply packet pass rate (PPR) to represent its reliability. Then, we analyze the SPS without sensing and present a theoretical expression of the reliability, which is described as a function of channel busy rate (CBR). Second, an iterative approach is applied to analyze the sensing-based SPS, and the mathematical expressions of lower and upper-reliability bounds are derived. Third, based on the existing condition of the upper bound, we propose a reliability improvement solution, which utilizes a distributed algorithm to process added information, such as the counter and the offset for the remaining storage space. Finally, this solution is applied to LTE-V2X, and simulation shows that the proposed scheme can significantly improve the scheduling reliability.

Design and Analysis of a Short-Term Sensing-Based Resource Selection Scheme for C-V2X Networks

The cellular vehicle-to-everything (C-V2X) networks can support direct vehicle-to-vehicle (V2V) communications via sidelink/PC5 interface without cellular infrastructure support. The sensing-based semipersistent scheduling (SPS) scheme is to allow vehicles to autonomously reserve and select radio resources. However, the common sensing nature of the distributed SPS algorithm gives rise to that C-V2X distributed communications can be challenged by the resource selection collisions, especially in aperiodic traffic, which results in low reliability. In this article, we propose a short-term sensing-based resource selection (STS-RS) scheme to reduce packet collisions due to resource contention, where a short-term sensing duration is configured at the beginning of the resource unit right before resource selection, and whether the packet is ultimately transmitted on the selected resource depends on the sensing result. Furthermore, analysis models of the performance for the proposed STS-RS scheme and SPS scheme defined in C-V2X mode 4 are investigated. Finally, simulations and numerical results show that the STS-RS scheme significantly reduces the packet collisions and increases the C-V2X direct communication performance compared to the SPS scheme.

Performance Evaluation of NOMA for Sidelink Cellular-V2X Mode 4 in Driver Assistance System With Crash Warning

This article presents the performance characteristics of a potential extension of sidelink cellular-vehicle-to-everything mode 4 (simply called mode 4) with uplink non-orthogonal multiple access (UL-NOMA), named SPS-NOMA, in driver assistance systems with a crash warning. In SPS-NOMA, multiple nodes (e.g., cars or pedestrians with communication equipment) simultaneously broadcast their data frames at a time-frequency resource selected by sensing-based semi-persistent scheduling (sensing-based SPS), the distributed random access protocol of mode 4. The transmitted signals are superposed at the receiver sides, and successive interference canceller (SIC) supports decoding the superposed signal. In SPS-NOMA, sensing-based SPS is expected to enhance the signal-to-interference-plus-noise ratio at each SIC iteration. The effect boosts the performance gains of the SIC in broadcast cases and mitigates the channel congestion. Our computer simulations highlighted that SPS-NOMA improved the performance of the ordinary mode 4 by 38% in the fundamental node distribution model. In conclusion, SPS-NOMA is expected to be the next generation sidelink C-V2X as the extended mode 4.

An Explicit Reservation-Augmented Resource Allocation Scheme for C-V2X Sidelink Mode 4

In the autonomous sidelink resource scheduling for Cellular V2X (C-V2X), the standard sensing-based semi-persistent scheduling (SPS) algorithm relies on several mechanisms such as random resource selection, resource utilization pattern monitoring, and probabilistic reselection to minimize packet collisions and to cope with vehicular topology changes. Even so, the collision probability is still not negligible, and its performance is far from the projected requirements for low latency and high reliability applications for future C-V2X communication. In this article, we propose a reservation mechanism that supplements the standard SPS for C-V2X Sidelink Mode 4, which visibly improves the performance in face of congestion and in the fringe of the communication range. In particular, we demonstrate that the reservation achieves the best performance if made much earlier than actual use of the reserved resource at least by an average of one second.