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Feedback Overhead-Aware Clustering for Interference Alignment in Multiuser Interference Networks
Byoung-Yoon MIN Heewon KANG Sungyoon CHO Jinyoung JANG Dong Ku KIM
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 2017/02/01
Online ISSN: 1745-1337
Type of Manuscript: LETTER
Category: Communication Theory and Signals
limited feedback, clustering, interference alignment,
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Interference alignment (IA) is a promising technology for eliminating interferences while it still achieves the optimal capacity scaling. However, in practical systems, the IA feasibility limit and the heavy signaling overhead obstructs employing IA to large-scale networks. In order to jointly consider these issues, we propose the feedback overhead-aware IA clustering algorithm which comprises two parts: adaptive feedback resource assignment and dynamic IA clustering. Numerical results show that the proposed algorithm offers significant performance gains in comparison with conventional approaches.