MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks

During last several years, mobile communications using mmWave spectrum have been intensively researched for 5G wireless networks. Now the mmWave wireless technologies are evolved into direct device-to-device communications for a single or multihop communication via Giga-bit links. Vehicular ad hoc n...

Full description

Bibliographic Details
Main Author: Wooseong Kim
Format: Article
Language:English
Published: Hindawi-Wiley 2018-01-01
Series:Wireless Communications and Mobile Computing
Online Access:http://dx.doi.org/10.1155/2018/2753025
id doaj-85a0ef64bf774946a96a49522faf3b90
record_format Article
spelling doaj-85a0ef64bf774946a96a49522faf3b902020-11-24T23:34:34ZengHindawi-WileyWireless Communications and Mobile Computing1530-86691530-86772018-01-01201810.1155/2018/27530252753025MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc NetworksWooseong Kim0Department of Computer Engineering, Gachon University, 1342 Seongnam-si, Gyeonggi, Republic of KoreaDuring last several years, mobile communications using mmWave spectrum have been intensively researched for 5G wireless networks. Now the mmWave wireless technologies are evolved into direct device-to-device communications for a single or multihop communication via Giga-bit links. Vehicular ad hoc networks (VANETs) are one of the most attractive areas to apply the direct mmWave communications. In this paper, we propose a Giga-V2V (GiV2V) network, in which vehicles query and deliver high quality video and sensor data of smart and self-driving cars using mmWave communications instead of current dedicated short-range communications (DSRC). In the GiV2V networks, vehicles probably form a grid topology along lanes of a road, which leads to align mmWave beams of the vehicles and cause mutual interference among them. As channel diversity can resolve effectively the interference between mmWave beams, we propose several heuristic algorithms for channel assignment of each beam in the GiV2V networks. We investigate the proposed algorithms using simulation and compare performance with well-known metaheuristic algorithms for this NP-Hard problem.http://dx.doi.org/10.1155/2018/2753025
collection DOAJ
language English
format Article
sources DOAJ
author Wooseong Kim
spellingShingle Wooseong Kim
MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
Wireless Communications and Mobile Computing
author_facet Wooseong Kim
author_sort Wooseong Kim
title MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
title_short MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
title_full MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
title_fullStr MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
title_full_unstemmed MC-GiV2V: Multichannel Allocation in mmWave-Based Vehicular Ad Hoc Networks
title_sort mc-giv2v: multichannel allocation in mmwave-based vehicular ad hoc networks
publisher Hindawi-Wiley
series Wireless Communications and Mobile Computing
issn 1530-8669
1530-8677
publishDate 2018-01-01
description During last several years, mobile communications using mmWave spectrum have been intensively researched for 5G wireless networks. Now the mmWave wireless technologies are evolved into direct device-to-device communications for a single or multihop communication via Giga-bit links. Vehicular ad hoc networks (VANETs) are one of the most attractive areas to apply the direct mmWave communications. In this paper, we propose a Giga-V2V (GiV2V) network, in which vehicles query and deliver high quality video and sensor data of smart and self-driving cars using mmWave communications instead of current dedicated short-range communications (DSRC). In the GiV2V networks, vehicles probably form a grid topology along lanes of a road, which leads to align mmWave beams of the vehicles and cause mutual interference among them. As channel diversity can resolve effectively the interference between mmWave beams, we propose several heuristic algorithms for channel assignment of each beam in the GiV2V networks. We investigate the proposed algorithms using simulation and compare performance with well-known metaheuristic algorithms for this NP-Hard problem.
url http://dx.doi.org/10.1155/2018/2753025
work_keys_str_mv AT wooseongkim mcgiv2vmultichannelallocationinmmwavebasedvehicularadhocnetworks
_version_ 1725528750305574912