Random Matrix Analysis of Future Multi Cell MU-MIMO Networks

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Axel Müller



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Future wireless communication systems will need to feature multi cellular heterogeneous architectures consisting of improved macro cells and very dense small cells, in order to support the exponentially rising demand for physical layer throughput. Such structures cause unprecedented levels of inter and intra cell interference, which needs to be mitigated or, ideally, exploited in order to improve overall spectral efficiency of the communication network. Techniques like massive multiple input multiple output (MIMO), cooperation, etc., that also help with interference management, will increase the size of the already large heterogeneous architectures to truly enormous networks, that defy theoretical analysis via traditional statistical methods.

Accordingly, in this thesis we will apply and improve the already known framework of large random matrix theory (RMT) to analyse the interference problem and propose solutions centred around new precoding schemes, which rely on large system analysis based insights. First, we will propose and analyse a new family of precoding schemes that reduce the computational precoding complexity of base stations equipped with a large number of antennas, while maintaining most of the interference mitigation capabilities of conventional close-tooptimal regularized zero forcing. Second, we will propose an interference aware linear precoder, based on an intuitive trade-off and recent results on multi cell regularized zero forcing, that allows small cells to effectively mitigate induced interference with minimal cooperation. In order to facilitate utilization of the analytic RMT approach for future generations of interested researchers, we will also provide a comprehensive tutorial on the practical application of RMT in communication problems.

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