Is It Worth to Use Feedback Channel in 5G V2X Platoon Scenarios?

TL;DR

Is It Worth to Use Feedback Channel in 5G V2X Platoon Scenarios? investigates whether the PSFCH feedback channel improves network capacity in a platoon scenario with groupcast DENMs and surrounding broadcast traffic. The authors model a highway 5G V2X network with Ng platoon members and Nb non-platoon UEs, run NS-3 simulations, define the capacity metric $C_g(\lambda_b)$ as the maximum groupcast load $\lambda_g$ that satisfies QoS constraints $PLR^b$ and $PLR^g$, and compare PSFCH-on versus PSFCH-off configurations across varying $\lambda_b$, $N_g$, and $D^{QoS}$. The results show that PSFCH can double capacity under favorable conditions (low broadcast load, small platoon, latency budgets larger than the ACK delay $D^{ACK}$) but can halve capacity under high broadcast load, large platoons, or tight $D^{QoS}$, highlighting the need for adaptive PSFCH parameter selection. The work provides actionable guidance for deploying PSFCH in future 5G V2X systems and motivates adaptive retransmission and MCS strategies.

Abstract

5G Vehicle-to-Everything (V2X) is a new technology developed by 3GPP to support inter-vehicle communication. In contrast to 4G V2X which allows only broadcast communication, 5G V2X enables groupcast and unicast communication. Such types of communication are needed for new V2X scenarios: platooning, extended sensors, remote driving, etc. To improve the data transmission reliability and assist in the selection of the transmission parameters in these scenarios, 5G V2X introduces a feedback channel that allows receivers to send acknowledgments in response to data packets. However, some part of the overall resource shall be allocated for the feedback channel, which reduces the amount of channel resources available for data transmission. In this paper, we consider a scenario with a platoon, which generates groupcast traffic, and surrounding vehicles, which generate legacy broadcast traffic. Using extensive simulations in NS-3, we analyze how the usage of the feedback channel influences the overall system capacity. Our results show that depending on the platoon size, groupcast, and broadcast traffic intensities, and their quality of service requirements, the usage of the feedback channel can in some cases significantly increase the system capacity (up to 2x), while in other cases it almost halves the system capacity. We explain the reasons for such effects and discuss how to adaptively select the feedback channel parameters.

Figures (6)

• Figure 1: Slot structure.
• Figure 2: The highway scenario.
• Figure 3: PLR as the function of $\lambda_g$.
• Figure 4: The network capacity as the function of broadcast traffic intensity $\lambda_b$.
• Figure 5: The network capacity as the function of platoon size $N_g$.