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- W2079584706 abstract "The main objective of this contribution is to develop a new interference alignment (IA) algorithm, which improves the sum-rate performance of multiuser MIMO communication systems. The recent iterative IA approaches cannot guarantee robust sum-rate performance in different K-user MIMO interference channels, especially at high SNR regime. In our proposed distributed optimization algorithm, each receiver maximizes the desired signal power while preserving the minimum interference leakage as a constraint. A convex relaxation has been applied to this optimization problem after reformulating it into semidefinite programming form. This algorithm provides orthogonal precoders and decoders, which is fairly simple in practical implementation. Simulation results of the proposed algorithm proffer significant sum-rate improvement in various interference channels compared to existing algorithms." @default.
- W2079584706 created "2016-06-24" @default.
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- W2079584706 date "2013-06-01" @default.
- W2079584706 modified "2023-10-17" @default.
- W2079584706 title "Min-maxing interference alignment algorithm as a semidefinite programming problem" @default.
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- W2079584706 doi "https://doi.org/10.1109/spawc.2013.6612058" @default.
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