Algorithms for Cell-Free Massive MIMO System

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Algorithms for Cell-Free Massive MIMO System

Cell-free massive MIMO (CF-MaMIMO) is a promising network architecture for energy efficient sixth generation (6G) wireless communication systems with uniform quality-of-service coverage and high data rates. It combines the benefits of distributed antenna systems (DAS) with those of centralized MaMIMO systems. In CF-MaMIMO, user equipments (UEs) communicate with a central processing unit (CPU) via geographically distributed access points (APs). The distributed topology of DAS enhances the attractive properties of centralized MaMIMO systems by reducing the average minimum distance between APs and UEs. This allows CF-MaMIMO systems to provide uniform high data rates over the coverage area and high energy efficiency.

For the success and the practical feasibility of CF-MaMIMO systems two aspects are crucial: First, the design of low-complexity decentralized receivers with performance comparable to centralized techniques and, second, the design of receivers robust to pilot contamination, a detrimental problem that appears when multiple users use simultaneously non-orthogonal pilot sequences for channel estimation.

In this project, we aim to develop new signal processing algorithms for CF-MaMIMO networks which attain the best trade-off between complexity and performance. We pursue this objective through a twofold approach, joint channel estimation and data detection on the one hand and Bayesian and/or deep learning on the other hand. The former approach enables substantial mitigation of pilot contamination whereas the latter allows tasks otherwise unaffordable to be performed with low complexity.

Tasks of the project

  • Study of the state of the art in CF-MaMIMO.
  • Implementation of new algorithms for the receiver such as channel estimation and data detection.
  • Theoretical and/or simulative performance analysis.

Prerequisites

  • Interest in communications and signal processing.
  • Basic knowledge of digital and mobile communication systems.
  • Programming skills in MATLAB.

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