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Optimizing the Resource Allocation of Periodic Messages With Different Sizes in LTE-V2V

Authors :
Alessandro Bazzi
Alberto Zanella
Barbara M. Masini
Source :
IEEE Access, Vol 7, Pp 43820-43830 (2019)
Publication Year :
2019
Publisher :
IEEE, 2019.

Abstract

Recently, 3GPP has added new features to long term evolution (LTE) that allow vehicles to communicate directly with each other and with surrounding objects. These short-range communications will play a key role in the so-called cellular vehicle-to-anything (C-V2X). As a particular service, which will be the basis of most applications for automated and connected cars, each vehicle will periodically broadcast information on its identity, status, and movements through short-range vehicle-to-vehicle (V2V) communications. Given the importance of this service, great attention has been given to the associated resource allocation procedures and the number of vehicles that can be simultaneously communicating in the network. However, little attention has been paid to handling messages of different sizes, which is actually foreseen in practice in order to transmit static information with a reduced periodicity. With this in mind, we evaluate the number of vehicles that can be allocated when parameters are optimized for messages of different sizes. This objective is pursued taking into account the numerous constraints imposed by the standard, through the formalization and solution of a combinatorial optimization problem. Example results, based on 3GPP indications, show that, with respect to the optimization of the allocation based on the larger packets, it is possible to obtain an increase that varies between 10% and 30%, depending on the conditions, with peaks above 150% in specific cases.

Details

Language :
English
ISSN :
21693536
Volume :
7
Database :
Directory of Open Access Journals
Journal :
IEEE Access
Publication Type :
Academic Journal
Accession number :
edsdoj.223b583d483543a6be401d7657343b7b
Document Type :
article
Full Text :
https://doi.org/10.1109/ACCESS.2019.2908248