Motivation:

Massive multiple-input multiple-output (MIMO) is a transmission technique that leverages a large number of base station antennas to support many single antenna users, e.g., in your smartphone. It may not possible to deploy such expensive and powerful hardware on every single antenna. Since the power consumption by ADCs grows exponentially with their resolution level, using one-bit ADCs may be a practical way of implementing cost-efficient and green massive MIMO systems.

Goal:

The aim of this thesis is first to do a literature research regarding one-bit massive MIMO detection and to implement several approaches for detection. Depending on the type and advancement in this work, also Machine Learning based approaches (Deep Neural Networks) can be investigated for application in this task.

Requirements:

In order to work on this thesis, a successful participation in the lectures Wireless Communications and Communication Technologies is required. Also, a solid understanding in linear algebra, optimization theory and stochastics is needed. Programming skills in Python and participation in the lecture Advanced Topics in Digital Communications are advantageous but not necessary.