On the design and deployment of multitier heterogeneous and adaptive vehicular networks

Shuja Ansari, Tuleen Boutaleb, Sinan Sinanovic, Carlos Gamio, Ioannis Krikidis

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    4 Citations (Scopus)
    251 Downloads (Pure)


    Research on connected and autonomous vehicles
    (CAVs) is moving towards first deployments around the world.
    For complete vehicle autonomy, on top of sensors there is a
    need for an effective communication system. Due to the critical
    safety, transmission requirements for these communications are
    stringent. In an urban environment, with high density of vehicles,
    standardized dedicated short range communications (DSRC)
    solely does not perform well. Avoiding costs for new DSRC
    infrastructure, heterogeneous networks integrating long term
    evolution (4G-LTE mobile network) and DSRC have shown
    promising results. With the ever increasing number of vehicles,
    an optimal integration is required in order to balance the capacity
    load on the two networks. This paper proposes a systematic
    approach to designing multitier heterogeneous adaptive vehicular
    (MHAV) networks. With extensive system level simulations modeling Glasgow city center, incorporating proposed algorithms,
    scaling of the network along with load balancing between LTE
    and DSRC have been investigated in this paper. With the design
    criteria proposed for MHAV, results show that under realistic
    conditions the probability of end-to-end communication delay to
    be less than 50 ms is above 90% for a density of 250 vehicles/km2.
    Original languageEnglish
    Title of host publication2018 11th International Symposium on Communication Systems, Networks and Digital Signal Processing, CSNDSP 2018
    ISBN (Electronic)9781538613351
    ISBN (Print)9781538613368
    Publication statusPublished - 27 Sept 2018


    • automotive engineering
    • autonomous vehicle

    ASJC Scopus subject areas

    • Signal Processing
    • Computer Networks and Communications


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