A novel safety message dissemination framework in LTE‐V2X system

Abstract

Vehicular communication plays a crucial role in improving road safety and maintaining traffic efficiency through the exchange of safety messages. Besides road safety, it can also be used to support other nonsafety features such as infotainment services, traffic management, parking assistance, and so on. In this article, we explore a hybrid long term evolution vehicle‐to‐everything architecture where we use both vehicle‐to‐infrastructure (V2I) and vehicle‐to‐vehicle (V2V) communication to simultaneously provide high throughput for infotainment services and maintain high reliability and low transmission delay for the safety messages. To this end, we propose V2I and V2V resource allocation algorithms which support a strict allocation priority for the safety messages over the nonsafety messages. We evaluate the performance of the proposed algorithms by extensive simulations using OMNeT++, INET, and SimuLTE softwares and analyze the simulation data using MATLAB software. The simulation results indicate that, as compared with using only V2I communication, the proposed algorithms decrease the end‐to‐end delay (∼23%, on average) of the safety messages with little degradation (< 10%, on average) in throughput of the background traffic. We compare our proposed algorithms with the existing algorithms and find that the proposed algorithms show a performance gain of 36.5% and 45% in terms of end‐to‐end latency and packet reception ratio, respectively.

Federated Learning Enabled SDN for Routing Emergency Safety Messages (ESMs) in IoV Under 5G Environment

“…ESMs are emergency warnings and delay-sensitive messages transmitted to the targeted vehicles when detecting hazardous events on the road to avoid crucial danger and road congestion [36]. The major challenge of ESM dissemination in traditional vehicular networks is high broadcast storms, which consume large amounts of bandwidth, increase network congestion, and further increase dissemination delay [37].…”

Resource allocation for cellular device‐to‐device‐aided vehicle‐to‐everything networks with partial channel state information

“…However, the limitation in the works discussed above is that in the actual environment, accurate CSI is hard to acquire, 22 especially for those non‐V2I links 23,24 . Besides, some works attempt to only consider large‐scale fading in order to simplify the model 25,26 . Obviously, the impact of fast fading should be taken into account; otherwise, the capacity performance of the real network will not be reflected.…”

“…23,24 Besides, some works attempt to only consider large-scale fading in order to simplify the model. 25,26 Obviously, the impact of fast fading should be taken into account; otherwise, the capacity performance of the real network will not be reflected. Although some subsequent studies consider incorporating statistical CSI into models, 23,24,27,28 these models only target the V2I or V2V link capacity alone, without exploring the performance on overall channel capacity under different weights.…”