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Weak-strong massive MIMO communication with low-resolution ADCs

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Hybrid architecture for enabling weak-strong communications for massive MIMO basestations equipped with low-resolution data converters.

Short Description

Massive multi-antenna (MIMO) technology is a cornerstone of current (5G) and future wireless communication systems that enables the operation of multiple users (MU) within the same time-frequency domain. However, the implementation of massive MIMO systems creates significant challenges in terms of power consumption, circuit complexity, and cost. To address these challenges, massive MIO basestations will have to rely on low-resolution analog-to-digital converters (ADCs). However, the use of such low-resolution ADCs creates new difficulties. One of them is the necessity of meticulous power control on the user side to ensure that the basestation receive signals are equally strong for all users. Otherwise, stronger users would simply drown weaker users in quantization noise.

The goal of this project is to alleviate the dependency on power control in low-resolution massive MU-MIMO systems by using an analog signal transform prior to data conversion. To this end, we will build on insights gained in our recent works on low-resolution jammer mitigation [1], [2]. After familiarizing yourself with these works, you will develop a linear transform suited for implementation in analog that can alleviate the burden of strong users on low-resolution ADCs while allowing the successful detection of all user signals.

[1] G. Marti, O. Castañeda, and C. Studer, "Jammer Mitigation via Beam-Slicing for Low-Resolution mmWave Massive MU-MIMO", IEEE Open Journal of Circuits and Systems, Vol. 2, pp. 820-832, Dec. 2021

[2] G. Marti, O. Castañeda, S. Jacobsson, G. Durisi, T. Goldstein, and C. Studer, "Hybrid Jammer Mitigation for All-Digital mmWave Massive MU-MIMO", 2021 Asilomar Conference on Signals, Systems, and Computers

Status: Available

Looking for 1-2 Semester/Master students
Contact: Gian Marti


A solid foundation in linear algebra
Familiarity with the basics of digital or wireless communication


20% Literature research
40% Algorithm development
40% MATLAB simulation


Christoph Studer

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Detailed Task Description


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