Generalized Interference Alignment—Part I: Theoretical Framework
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Win_Generalized interference I.pdf
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801.91 KB
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Author(s) • •
Lau, Vincent K. N.
Ruan, Liangzhong
Win, Moe Z
Date Issued
May 2016
Journal
IEEE Transactions on Signal Processing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Ruan, Liangzhong, Vincent K. N. Lau, and Moe Z. Win. “Generalized Interference Alignment—Part I: Theoretical Framework.” IEEE Transactions on Signal Processing 64.10 (2016): 2675–2687.
Version
Original manuscript
Abstract
Interference alignment (IA) has attracted enormous research interest as it achieves optimal capacity scaling with respect to signal to noise ratio on interference networks. IA has also recently emerged as an effective tool in engineering interference for secrecy protection on wireless wiretap networks. However, despite the numerous works dedicated to IA, two of its fundamental issues, i.e., feasibility conditions and transceiver design, are not completely addressed in the literature. In this two part paper, a generalized interference alignment (GIA) technique is proposed to enhance the IA's capability in secrecy protection. A theoretical framework is established to analyze the two fundamental issues of GIA in Part I and then the performance of GIA in large-scale stochastic networks is characterized to illustrate how GIA benefits secrecy protection in Part II. The theoretical framework for GIA adopts methodologies from algebraic geometry, determines the necessary and sufficient feasibility conditions of GIA, and generates a set of algorithms for solving the GIA problem. This framework sets up a foundation for the development and implementation of GIA.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Creative Commons Attribution-Noncommercial-Share Alike
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DOI of Published Version
https://doi.org/10.1109/tsp.2015.2474301