Optimal Distributed Beamforming for MISO Interference Channels
Jiaming Qiu, Rui Zhang, Zhi-Quan Luo, and Shuguang Cui
TL;DR
This paper introduces two new distributed algorithms for optimal beamforming in MISO interference channels, enabling efficient and convergent solutions to the Pareto boundary problem through parallel and localized computations.
Contribution
The paper presents novel distributed algorithms using alternating and cyclic projections for optimal beamforming in MISO interference channels, with proven convergence.
Findings
Algorithms successfully compute Pareto optimal boundary
Both algorithms converge reliably
Distributed methods improve computational efficiency
Abstract
We consider the problem of quantifying the Pareto optimal boundary in the achievable rate region over multiple-input single-output (MISO) interference channels, where the problem boils down to solving a sequence of convex feasibility problems after certain transformations. The feasibility problem is solved by two new distributed optimal beamforming algorithms, where the first one is to parallelize the computation based on the method of alternating projections, and the second one is to localize the computation based on the method of cyclic projections. Convergence proofs are established for both algorithms.
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