Maximum-Service Channel Assignment in Vehicular Radar-Communication | IEEE Journals & Magazine | IEEE Xplore

Maximum-Service Channel Assignment in Vehicular Radar-Communication


Visual illustration of channel assignment to a cluster of radar/communication vehicles over shared spectrum where vehicles are allowed to share the same channel as long a...

Abstract:

Spectrum sharing between different technologies has become a necessity as the RF spectrum has become more congested than ever due to the increasing number of connected de...Show More

Abstract:

Spectrum sharing between different technologies has become a necessity as the RF spectrum has become more congested than ever due to the increasing number of connected devices and applications all wishing to access the spectrum simultaneously. Vehicular networks are one of many scenarios of spectrum sharing as vehicles are expected to share the same spectrum for radar sensing and communication purposes. Channel assignment among radar sensors and communication transceivers in automotive systems is crucial for the success of future vehicular networks. This paper proposes an optimization framework for the channel assignment to multiple automotive radars and communication transceivers aiming at maximizing the number of served vehicles under hard quality of service requirements. The channel assignment problem is formulated as an integer linear optimization with binary variables. A heuristic solution that is based on ordered sequential channel assignment (OSCA) is proposed and is shown to achieve at least 92% of the solution obtained from branch-and-cut based techniques with much less computational complexity and run-time; at most 2% of the run-time of branch-and-cut.
Visual illustration of channel assignment to a cluster of radar/communication vehicles over shared spectrum where vehicles are allowed to share the same channel as long a...
Published in: IEEE Access ( Volume: 9)
Page(s): 138359 - 138370
Date of Publication: 08 October 2021
Electronic ISSN: 2169-3536

Funding Agency:


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