On the Impact of Hardware Impairments on Massive MIMO
Paper in proceedings, 2014

Massive multi-user (MU) multiple-input multiple-output (MIMO) systems are one possible key technology for next generation wireless communication systems. Claims have been made that massive MU-MIMO will increase both the radiated energy efficiency as well as the sum-rate capacity by orders of magnitude, because of the high transmit directivity. However, due to the very large number of transceivers needed at each base-station (BS), a successful implementation of massive MU-MIMO will be contingent on of the availability of very cheap, compact and power-efficient radio and digital-processing hardware. This may in turn impair the quality of the modulated radio frequency (RF) signal due to an increased amount of power-amplifier distortion, phase-noise, and quantization noise. In this paper, we examine the effects of hardware impairments on a massive MU-MIMO single-cell system by means of theory and simulation. The simulations are performed using simplified, well-established statistical hardware impairment models as well as more sophisticated and realistic models based upon measurements and electromagnetic antenna array simulations.

5G

Radio Frequency Power Amplifier

Digital to Analogue Conversion

Massive MIMO

Author

Ulf Gustavsson

Cesar Sanchez Perez

Chalmers, Microtechnology and Nanoscience (MC2), Microwave Electronics

Thomas Eriksson

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Fredrik Athley

Giuseppe Durisi

Chalmers, Signals and Systems, Communication and Antenna Systems, Communication Systems

Katharina Hausmair

GigaHertz Centre

Christian Fager

Chalmers, Microtechnology and Nanoscience (MC2), Microwave Electronics

Lars Svensson

Chalmers, Computer Science and Engineering (Chalmers), Computer Engineering (Chalmers)

IEEE Globecom 2014 Workshop - Massive MIMO: From Theory to Practice, 2014-12-08, Austin, Texas, USA

294-300

Areas of Advance

Information and Communication Technology

Subject Categories

Communication Systems

Signal Processing

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/GLOCOMW.2014.7063447

ISBN

978-147997470-2

More information

Created

10/7/2017