### Skapa referens, olika format (klipp och klistra)

**Harvard**

Zhang, X., Matthaiou, M., Coldrey, M. och Björnson, E. (2014) *Energy efficiency optimization in hardware-constrained large-scale MIMO systems*.

** BibTeX **

@conference{

Zhang2014,

author={Zhang, Xinlin and Matthaiou, Michail and Coldrey, M. and Björnson, E.},

title={Energy efficiency optimization in hardware-constrained large-scale MIMO systems},

booktitle={2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings},

isbn={978-147995863-4},

pages={992-996},

abstract={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.},

year={2014},

}

** RefWorks **

RT Conference Proceedings

SR Electronic

ID 208843

A1 Zhang, Xinlin

A1 Matthaiou, Michail

A1 Coldrey, M.

A1 Björnson, E.

T1 Energy efficiency optimization in hardware-constrained large-scale MIMO systems

YR 2014

T2 2014 11th International Symposium on Wireless Communications Systems, ISWCS 2014 - Proceedings

SN 978-147995863-4

SP 992

OP 996

AB 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.

LA eng

DO 10.1109/ISWCS.2014.6933498

LK http://dx.doi.org/10.1109/ISWCS.2014.6933498

OL 30