Impact of Quantized Side Information on Subchannel Scheduling for Cellular V2X

TL;DR

This paper investigates how quantizing side information affects subchannel scheduling in cellular V2X communications, proposing a 3-bit quantization scheme that maintains performance while reducing complexity.

Contribution

It introduces a graph-based semi-persistent scheduling method utilizing quantized SINR measurements for mode-3 C-V2X, demonstrating effective performance with minimal quantization bits.

Findings

3 bits per vehicle every 100 ms suffice for effective scheduling

Quantized side information maintains performance comparable to unquantized data

Proposed algorithm outperforms pseudo-random and greedy SPS methods

Abstract

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 \textit{mode-3}, requires support from eNodeBs in order to realize subchannel scheduling. This paper discusses a graph theoretical approach for semi-persistent scheduling (SPS) in \textit{mode-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.