Link Level Analysis of NR V2X Sidelink Communications

The Internet of Vehicles (IoV) will interconnect vehicles, vulnerable road users, and infrastructure nodes for a safer, more efficient, and digitalized mobility. In the IoV vision, traditional network-based communications will be complemented with direct Sidelink (SL) Vehicle-to-Everything (V2X) communications. To this aim, 3GPP introduced in Release 16 the New Radio (NR) V2X SL technology. The NR V2X SL standard includes important Physical (PHY) layer novelties with respect to LTE V2X SL and NR Uplink/Downlink, and is characterized by a large set of configurable parameters. However, existing NR V2X SL link level studies focus on a confined set of configurations. This limits a thorough understanding of the NR V2X SL link level performance and impacts the accuracy of system level evaluations, which typically leverage link level models to accurately represent the PHY layer performance. These models are based on Look-Up Tables (LUTs) that map the link level performance, e.g., BLock Error Rate (BLER), as a function of the link quality, e.g., Signalto-Noise Ratio (SNR). This study presents an exhaustive NR V2X SL link level evaluation that analyzes the impact of relevant PHY layer aspects, e.g., modulation and coding scheme, channel model, and transmitter-receiver relative speed, considering the wide set of configurations recommended by 3GPP and ETSI. The obtained standard-compliant LUTs are openly released, representing the largest NR V2X SL link level dataset available. The released dataset represents a valuable asset for the community, as it allows exhaustive NR V2X SL system level investigations under a broad range of settings and configurations

On the Impact of Re-Evaluation in 5G NR V2X Mode 2

5G NR V2X has been designed to support advanced connected and automated driving V2X services. These services are characterized by variable traffic patterns that can generate packet collisions in decentralized systems where vehicles autonomously select their radio resources like 5G NR V2X mode 2. 5G NR V2X introduces a re-evaluation mechanism at the MAC layer to detect and avoid possible packet collisions before a vehicle transmits in selected resources. Most of the studies conducted to date on 5G NR V2X do not consider the re-evaluation mechanism despite being a mandatory MAC feature. This article advances the state of the art with an in-depth analysis and evaluation of the operation and performance of re-evaluation in 5G NR V2X mode 2 under different traffic patterns and mode 2 configurations. The study shows that re-evaluation is effective in avoiding collisions with periodic traffic but its effectiveness decreases with aperiodic traffic and of variable size. The study also shows that re-evaluation is effective in avoiding collisions generated by the retransmission of packets. However, its overall impact on the performance of 5G NR V2X mode 2 is small, while it can have a relevant implementation cost due to the frequent re-evaluation checks and resource reselections. This raises questions on the current design of the re-evaluation mechanism that is a mandatory feature in 5G NR V2X mode 2

End-to-End V2X Latency Modeling and Analysis in 5G Networks

networks provide higher flexibility and improved performance compared to previous cellular technologies. This has raised expectations on the possibility to support advanced Vehicle to Everything (V2X) services using the cellular network via Vehicle-to-Network (V2N) and Vehicle-to-Network-to-Vehicle (V2N2V) connections. The possibility to support critical V2X services using 5G V2N2V or V2N connections depends on their end-to-end (E2E) latency. The E2E latency of V2N2V or V2N connections depends on the particular 5G network deployment, dimensioning and configuration, in addition to the network load. To date, few studies have analyzed the capabilities of V2N2V or V2N connections to support critical V2X services, and most of them focus on the 5G radio access network or consider dedicated 5G pilot deployments under controlled conditions. This paper progresses the state-of-the-art by introducing a novel E2E latency model to quantify the latency of 5G V2N and V2N2V communications. The model includes the latency introduced at the radio, transport, core, Internet, peering points and application server (AS) when vehicles are supported by a single mobile network operator (MNO) and when they are supported by multiple MNOs. The model can quantify the latency experienced when the V2X AS is deployed from the edge of the network (using MEC platforms) to the cloud. Using this model, this study estimates the E2E latency of 5G V2N2V connections for a large variety of possible 5G network deployments and configurations. The analysis helps identify which 5G network deployments and configurations are more suitable to meet V2X latency requirements. To this aim, we consider as case study the cooperative lane change service. The conducted analysis highlights the challenge for centralized network deployments that locate the V2X AS at the cloud to meet the latency requirements of advanced V2X services. Locating the V2X AS closer to the cell edge reduces the latency. However, it requires a higher number of ASs and also a careful dimensioning of the network and its configuration to ensure sufficient network and AS resources are dedicated to serve the V2X traffic