# Impact of Quantized Side Information on Subchannel Scheduling for Cellular V2X

arXiv: https://arxiv.org/abs/1807.04830 · HTML: https://mlsanity.com/paper/1807.04830/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Multi-Timescale Control and Communications with Deep Reinforcement Learning -- Part I: Communication-Aware Vehicle Control](https://mlsanity.com/paper/2311.11281/) (2023)

## Abstract (arXiv)

In Release 14, 3GPP completed a first version of cellular vehicle--to--everything (C-V2X) communications wherein two modalities were introduced. One of these schemes, known as textitmode-3, requires support from eNodeBs in order to realize subchannel scheduling. This paper discusses a graph theoretical approach for semi-persistent scheduling (SPS) in textitmode-3 harnessing a sensing mechanism whereby vehicles can monitor signal--to--interference--plus--noise ratio (SINR) levels across sidelink subchannels. eNodeBs request such measurements from vehicles and utilize them to accomplish suitable subchannel assignments. However, since SINR values---herein also referred to as side information---span a wide range, quantization is required. We conclude that 3 bits per vehicle every 100 ms can provide sufficient granularity to maintain appropriate performance without severe degradation. Furthermore, the proposed algorithm is compared against pseudo-random and greedy SPS algorithms.