Interference alignment via Feasible Point Pursuit

Aritra Konar, Ruoyu Sun, Nicholas D. Sidiropoulos, Zhi Quan Luo

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

Abstract

Designing iterative algorithms for interference alignment (IA) is very useful for both practical and theoretical purposes. However, the existing works on iterative IA algorithms have not reported significant gains in terms of the DoF (Degrees of Freedom) over simple orthogonalization schemes. In this paper, we aim to design an iterative IA algorithm that can achieve high DoF. We recast the problem of designing linear transceivers for interference alignment as a non-convex quadratic feasibility problem, and apply an extension of the recently proposed Feasible Point Pursuit Successive Convex Approximation (FPP-SCA) algorithm [8] to solve it. Simulations suggest that the proposed algorithm can attain DoF very close to the known theoretical upper bound in certain cases, significantly outperforming existing approaches.

Original languageEnglish (US)
Title of host publicationSPAWC 2015 - 16th IEEE International Workshop on Signal Processing Advances in Wireless Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages640-644
Number of pages5
ISBN (Electronic)9781479919307
DOIs
StatePublished - Aug 27 2015
Event16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2015 - Stockholm, Sweden
Duration: Jun 28 2015Jul 1 2015

Publication series

NameIEEE Workshop on Signal Processing Advances in Wireless Communications, SPAWC
Volume2015-August

Other

Other16th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2015
Country/TerritorySweden
CityStockholm
Period6/28/157/1/15

Keywords

  • Algorithm design and analysis
  • Approximation algorithms
  • Approximation methods
  • Integrated circuits
  • Interference
  • MIMO
  • Signal processing algorithms

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