Evidence map›Paper›PMID 38257430›Full record

ReviewSensors (Basel, Switzerland)2024

Empowering the Vehicular Network with RIS Technology: A State-of-the-Art Review.

Farheen Naaz, Ali Nauman, Tahir Khurshaid, Sung-Won Kim

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Farheen NaazInformation and Communication Engineering Department, Yeungnam University, Gyeongsan 38541, Republic of Korea.
Ali NaumanInformation and Communication Engineering Department, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0002-2133-5286
Tahir KhurshaidDepartment of Electrical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0001-6113-123X
Sung-Won KimInformation and Communication Engineering Department, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0001-8454-6980

Funding

This work was supported by the 2023 Yeungnam University Research Grant
6 · The paper itself

Abstract

Reconfigurable intelligent surfaces (RIS) are expected to bring about a revolutionary transformation in vehicular networks, thus paving the way for a future characterized by connected and automated vehicles (CAV). An RIS is a planar structure comprising many passive elements that can dynamically manipulate electromagnetic waves to enhance wireless communication by reflecting, refracting, and focusing signals in a programmable manner. RIS exhibits substantial potential for improving vehicle-to-everything (V2X) communication through various means, including coverage enhancement, interference mitigation, improving signal strength, and providing additional layers of privacy and security. This article presents a comprehensive survey that explores the emerging opportunities arising from the integration of RIS into vehicular networks. To examine the convergence of RIS and V2X communications, the survey adopted a holistic approach, thus highlighting the potential benefits and challenges of this combination. In this study, we examined several applications of RIS-aided V2X communication. Subsequently, we delve into the fundamental emerging technologies that are expected to empower vehicular networks, encompassing mobile edge computing (MEC), non-orthogonal multiple access (NOMA), millimeter-wave communication (mmWave), Artificial Intelligence (AI), and visible light communication (VLC). Finally, to stimulate further research in this domain, we emphasize noteworthy research challenges and potential avenues for future exploration.

Indexed as

autonomous vehiclesintelligent transportation systemMECNOMAphysical layer security (PLS)platooningreconfigurable intelligent surfacevehicle-to-everything

Identifiers

PMID38257430
PMCPMC10820961

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.