Efficient Delivery of Massive Small-Data in C-V2X Networks: A Supplementary Participant Selection Mechanism

Amid the proliferation of connected vehicles and escalating traffic, the 5G Cellular Vehicle-to-Everything (C-V2X) research community prioritizes efficient small-data delivery mechanisms to ensure the rapid dissemination of emergency information to vehicles and drivers. Uni-Multi-Unicast (UMUcast) has emerged as a promising 5G C-V2X solution, enabling the simultaneous transmission of diverse small-data to designated receivers, thereby enhancing cell capacity and throughput. However, UMUcast suffers from notable drawbacks, including high inhibition overhead for non-participants, excessive energy consumption, and an inability to deliver multiple small-data packets to a single vehicle at the same time. This paper proposes eXplicit UMUcast (XUMUcast), an enhanced UMUcast framework incorporating explicit extension headers into each UMUcast chunk. XUMUcast integrates a Bloom filter (BF)-based group membership mechanism with a Chinese remainder theorem (CRT)-based data aggregation algorithm. Simulation results demonstrate that XUMUcast outperforms UMUcast by 1) offloading data traffic from the radio channel; 2) reducing computational power and processing time consumption for non-participating in-group vehicles, and 3) enabling the delivery of multiple small-data messages to specific vehicles.