Iterative Reweighted Least Squares approach to interference alignment

Mohamed Rihan, Maha Elsabrouty, Said Elnouby, Hossam Shalaby, Osamu Muta, Hiroshi Furukawa

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

3 Citations (Scopus)


This paper investigates the interference alignment (IA) solution for a K-user static flat-fading multiple input multiple output (MIMO) interference channel. Optimal users' precoders and postcoders are designed through a rank constraint rank minimization (RCRM) framework with IA conditions inserted within the constraints and the cost function of a complex matrix optimization problem. With RCRM formulation, the interference is forced to span the lowest dimensional subspace possible, under the condition that the useful signal subspaces span all available spatial dimensions. Using the recent advances in matrix completion theory and low rank matrix recovery theory, we propose an Iterative Reweighted Least Squares (IRLS) approach to IA. Through this approach, we provide an adequate relaxation for the rank function which in some cases attain the same results obtained using the standard nuclear norm with lower elapsed time per iteration and lower number of iterations and in some cases perform better than any of the previous approaches.

Original languageEnglish
Title of host publication2013 IFIP Wireless Days, WD 2013
PublisherIEEE Computer Society
ISBN (Print)9781479905423
Publication statusPublished - 2013
Event6th IFIP/IEEE Wireless Days Conference, WD 2013 - Valencia, Spain
Duration: Nov 13 2013Nov 15 2013

Publication series

NameIFIP Wireless Days
ISSN (Print)2156-9711
ISSN (Electronic)2156-972X


Conference6th IFIP/IEEE Wireless Days Conference, WD 2013

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Signal Processing
  • Electrical and Electronic Engineering


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