Cited by 4Vehicular Ad Hoc Networks (VANETs)Traffic control and managementAdvanced Wireless Network Optimization

A novel method on resource allocation for V2X

Xing, Weimin, He, Haigang, Lu, Youxiong, Yang, Jin, Hu, Yuzhou, Chen, Lin·2020·2020 International Wireless Communications and Mobile Computing (IWCMC)

Abstract

This paper proposes an enhanced resource allocation mechanism on vehicle to anything (V2X) communication in Mode 2. In Mode 2, a kind of user equipment (UE) autonomous resource selection mode, the UE selects the actual transmission resources from one or more (pre-)configured resource pools based on sensing. The enhanced resource allocation mechanism proposed in this paper is able to allocate the sidelink resource intelligently based on not only the geographic location information but also the local digital map information, e.g., the road direction. This paper also investigates legacy zone based resource allocation mechanism which is only based on the geographic location information of the UE. The metric of packet reception rate (PRR) is used to quantify and compare the performance of the proposed resource allocation mechanism and the legacy mechanism in urban scenario with periodic and aperiodic traffic. Simulation results testify that the proposed enhanced resource allocation mechanism exhibits better performance than the zone based resource allocation mechanism. The proposed mechanism can reduce the interference among UEs, especially alleviate the in-band emission (IBE).

Integrity signals

Registry

Crossref · 10.1109/iwcmc48107.2020.9148108

Cites

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

We couldn’t retrieve this paper’s full text, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Geo-based scheduling leverages vehicles' geographical information to optimize resource allocation, improving communication efficiency and reducing interference in 6G V2X sidelink communication.

    “Geo-based scheduling [114], [9], [115] is an emerging resource allocation scheme for 6G V2X sidelink communication.It leverages the vehicles' geographical information to optimize resource allocation, improving communication efficiency and reducing interference.”
  • Zone-based resource allocation leverages geographical information to divide the vehicular network into zones and allocate resources to users within each zone based on traffic demand and channel conditions, with the goal of enhancing resource utilization, reducing interference, and optimizing overall system throughput.

    “Zone-based resource allocation [116], [9], [115] is an innovative scheme tailored for 6G V2X sidelink communication.It leverages the geographical information of the vehicles to divide the vehicular network into zones and efficiently allocate resources to users within each zone based on traffic demand and channel conditions.”

Cited by

Sorted by citations

Authors
Xing, W., He, H., Lu, Y., Yang, J., Hu, Y., & Chen, L.
Affiliations
ZTE (China) (CN)
Venue
2020 International Wireless Communications and Mobile Computing (IWCMC)
Publisher
IEEE
Published
2020-06
Pages
18-23
OpenAlex
W3046046459
Cited by
4
References
0
Citations by year
2025: 1 · 2024: 1 · 2022: 1 · 2021: 1
FWCI
0.70
Type
conference paper
Language
en
Open access
closed
Locations
International Wireless Communications and Mobile Computing Conference (IWCMC) (publishedVersion)
Topics
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Vehicular Ad Hoc Networks (VANETs)
  • Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
  • Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Network Optimization
Keywords
vehicle-to-everything communication, resource allocation, sidelink, Mode 2, resource pools, packet reception rate, interference suppression, urban traffic

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review