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About this paper
Vojtech Neuman, Miloslav Capek, Lukas Jelinek, Anu Lehtovuori, Ville Viikari
Researchers at Czech Technical University in Prague and Aalto University developed a theoretical framework for optimizing Multiple-Input-Multiple-Output (MIMO) antenna clusters by adjusting feeding coefficients. This framework, based on quadratically constrained quadratic programming, allows for a controlled balance between total efficiency, the envelope correlation coefficient, and power allocation across communication channels, demonstrated on both idealized dipole arrays and a realistic mobile terminal model.
Key insights
- An inherent and quantifiable trade-off exists between maximizing total efficiency and minimizing the envelope correlation coefficient in MIMO antenna clusters.
- Feeding optimization within multi-port antenna clusters provides sufficient degrees of freedom to systematically balance critical MIMO performance parameters, leveraging mutual coupling rather than solely suppressing it.
- The framework provides Pareto optimal frontiers for a given antenna geometry, allowing designers to understand the fundamental performance limits and make informed trade-offs between efficiency and correlation.
Summary by alphaXiv.
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