Capacity analysis of interfering channels

O. Durmaz, P.G. Jansen, S.O. Dulman, Sape J. Mullender

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    Abstract

    The current literature on multi-channel protocols in wireless networks mostly assume perfect orthogonality among different channels. However, channel orthogonality depends on factors like transceiver characteristics, transmission power, distance between transmitters, etc. In this paper we investigate the impact of channel orthogonality on the network capacity by simulations. We explore the difference in capacity of the orthogonal channels and interfering channels.We use an interference model which is based on extensive measurements on an example radio platform. Simulation results show that the achievable overall network capacity with realistic interfering channels can be close to the capacity of idealistic orthogonal channels depending how much the receiver is prone to the adjacent channel interference. This is an important implication since the careful use of interfering channels can provide better utilization of the spectrum.
    Original languageUndefined
    Title of host publicationProceedings of the 2nd ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks
    Place of PublicationNew York USA
    PublisherAssociation for Computing Machinery (ACM)
    Pages11-18
    Number of pages8
    ISBN (Print)978-1-59593-805-3
    DOIs
    Publication statusPublished - 2007

    Publication series

    Name
    PublisherACM
    NumberLNCS4549

    Keywords

    • EWI-11323
    • METIS-242209
    • IR-61994
    • CAES-PS: Pervasive Systems

    Cite this

    Durmaz, O., Jansen, P. G., Dulman, S. O., & Mullender, S. J. (2007). Capacity analysis of interfering channels. In Proceedings of the 2nd ACM workshop on Performance monitoring and measurement of heterogeneous wireless and wired networks (pp. 11-18). [10.1145/1298275.1298278] New York USA: Association for Computing Machinery (ACM). https://doi.org/10.1145/1298275.1298278