Selective interference alignment for MIMO cognitive femtocell networks

Basak Guler, Aylin Yener

    Research output: Contribution to journalArticlepeer-review

    63 Scopus citations


    This paper presents a novel cross-tier interference management solution for coexisting two-tier networks by exploiting cognition and coordination between tiers via the use of agile radios. The cognitive users sense their environment to determine the receivers they are interfering with, and adapt to it by designing their precoders using interference alignment (IA) in order to avoid causing performance degradation to nearby receivers. The proposed approach judiciously chooses the set of users to be aligned at each receiver as a subset of the cross-tier interferers, hence is termed selective IA. The proposed solution includes identification of the subspace in which cross-tier interference signals would be aligned followed by a distributed algorithm to identify the precoders needed at the selected interferers. The intra-tier interference is then dealt with using minimum mean squared error (MMSE) interference suppression. Numerical results demonstrate the effectiveness of selective IA for both uplink and downlink interference management.

    Original languageEnglish (US)
    Article number6683129
    Pages (from-to)439-450
    Number of pages12
    JournalIEEE Journal on Selected Areas in Communications
    Issue number3
    StatePublished - Mar 2014

    All Science Journal Classification (ASJC) codes

    • Computer Networks and Communications
    • Electrical and Electronic Engineering


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