Applications of Large Random Matrices in Communications Engineering
Ralf R. M\"uller, Giusi Alfano, Benjamin M. Zaidel, Rodrigo de Miguel

TL;DR
This paper reviews advanced mathematical tools like free probability and random matrix theory for analyzing large communication systems, providing insights into eigenvalue distributions, detector design, and channel modeling.
Contribution
It introduces a comprehensive overview of analytical methods from probability, operator algebra, and physics, applied specifically to large vector channel communication systems.
Findings
Eigenvalue distributions for large random matrices are characterized.
Analytic tools are applied to optimize multiuser detectors.
Models for scattering in dual antenna communication channels are developed.
Abstract
This work gives an overview of analytic tools for the design, analysis, and modelling of communication systems which can be described by linear vector channels such as y = Hx+z where the number of components in each vector is large. Tools from probability theory, operator algebra, and statistical physics are reviewed. The survey of analytical tools is complemented by examples of applications in communications engineering. Asymptotic eigenvalue distributions of many classes of random matrices are given. The treatment includes the problem of moments and the introduction of the Stieltjes transform. Free probability theory, which evolved from non-commutative operator algebras, is explained from a probabilistic point of view in order to better fit the engineering community. For that purpose freeness is defined without reference to non-commutative algebras. The treatment includes additive and…
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Taxonomy
TopicsRandom Matrices and Applications · Sparse and Compressive Sensing Techniques · Blind Source Separation Techniques
