Efficient Resource Allocation Scheme for Aperiodic Traffic in NR V2X Communications Through Adaptive Reservation and Selection

New Radio Vehicle-to-Everything(NR V2X) Mode 2 communication of the 3rd Generation Partnership Project(3GPP) has focused on the distributed resource allocation technique for the aperiodic traffic. However, due to the unpredictable generation intervals of the aperiodic traffic, it is challenging to predict accurately the random arrival moment as done in the periodic traffic, resulting in ineffective resource allocation when using the traditional Sensing-Based Semi-Persistent Scheduling (SB-SPS) scheme. Besides, the state-of-art reservation techniques with a changeable Resource Reservation Interval (RRI) seem not sufficient to handle intensive impacts of both selection collision and extra collision-induced delay between vehicular UEs during an aperiodic traffic transmission. In order to meet the low-latency and high-reliable QoS requirements of aperiodic traffic traffic in NR V2X Mode 2 communication, it is worthwhile in this paper to propose a novel effective resource allocation scheme namely ARSAP through the adaptive Reselection Counter (RC) and RRI adjustment, which is optimized by the joint critical value detection on both packet collision ratio and collision-induced persistent delay. Furthermore, a novel adaptive resource reservation technique with a matched RRI set related to RC and RRI adjustment can be designed to effectively accommodate the resource allocation for the upcoming aperiodic traffic. In addition, both the theoretical derivation of the performance metric and the simulated evaluation results are also given. It can be seen that the new proposed algorithm can achieve superior communication qualities such as high Packet Reception Ratio(PRR) and low delay to the counterparts, even in the highly-dense vehicular networks.