A significant limitation of the LTE-V2X and NR-V2X sidelink scheduling
mechanisms is their difficulty coping with variations in inter packet arrival
times, also known as aperiodic packets. This conflicts with the fundamental
characteristics of most V2X services which are triggered based on an event.
e.g. ETSI Cooperative Awareness Messages (CAMs) - vehicle kinematics,
Cooperative Perception Messages (CPMs) - object sensing and Decentralised Event
Notification Messages (DENMs) - event occurrences. Furthermore, network
management techniques such as congestion control mechanisms can result in
varied inter packet arrival times. To combat this, NR-V2X introduced a dynamic
grant mechanism, which we show is ineffective unless there is background
periodic traffic to stabilise the sensing history upon which the scheduler
makes it decisions. The characteristics of V2X services make it implausible
that such periodic application traffic will exist.
To overcome this significant drawback, we demonstrate that the standardised
scheduling algorithms can be made effective if the event triggered arrival rate
of packets can be accurately predicted. These predictions can be used to tune
the Resource Reservation Interval (RRI) parameter of the MAC scheduler to
negate the negative impact of aperiodicity. Such an approach allows the
scheduler to achieve comparable performance to a scenario where packets arrive
periodically. To demonstrate the effectiveness of our approach, an ML model has
been devised for the prediction of cooperative awareness messages, but the same
principle can be abstracted to other V2X service types.Comment: 9 pages, 10 figure