Energy efficiency optimization in hardware-constrained large-scale MIMO systems
Paper in proceeding, 2014

Large-scale multiple-input multiple-output (MIMO) communication systems can bring substantial improvement in spectral efficiency and/or energy efficiency, due to the excessive degrees-of-freedom and huge array gain. However, large-scale MIMO is expected to deploy lower-cost radio frequency (RF) components, which are particularly prone to hardware impairments. Unfortunately, compensation schemes are not able to remove the impact of hardware impairments completely, such that a certain amount of residual impairments always exists. In this paper, we investigate the impact of residual transmit RF impairments (RTRI) on the spectral and energy efficiency of training-based point-to-point large-scale MIMO systems, and seek to determine the optimal training length and number of antennas which maximize the energy efficiency. We derive deterministic equivalents of the signal-to-noise-and-interference ratio (SINR) with zero-forcing (ZF) receivers, as well as the corresponding spectral and energy efficiency, which are shown to be accurate even for small number of antennas. Through an iterative sequential optimization, we find that the optimal training length of systems with RTRI can be smaller compared to ideal hardware systems in the moderate SNR regime, while larger in the high SNR regime. Moreover, it is observed that RTRI can significantly decrease the optimal number of transmit and receive antennas.

Author

Xinlin Zhang

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Michail Matthaiou

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

Mikael Coldrey

Ericsson

E. Björnson

Linköping University

2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings

992-996
978-147995863-4 (ISBN)

Subject Categories

Signal Processing

DOI

10.1109/ISWCS.2014.6933498

ISBN

978-147995863-4

More information

Latest update

11/19/2018