Multipair Full-Duplex Relaying With Massive Arrays and Linear Processing
Journal article, 2014

We consider a multipair decode-and-forward relay channel, where multiple sources transmit simultaneously their signals to multiple destinations with the help of a full-duplex relay station. We assume that the relay station is equipped with massive arrays, while all sources and destinations have a single antenna. The relay station uses channel estimates obtained from received pilots and zero-forcing (ZF) or maximum-ratio combining/maximum-ratio transmission (MRC/MRT) to process the signals. To significantly reduce the loop interference effect, we propose two techniques: i) using a massive receive antenna array; or ii) using a massive transmit antenna array together with very low transmit power at the relay station. We derive an exact achievable rate expression in closed-form for MRC/MRT processing and an analytical approximation of the achievable rate for ZF processing. This approximation is very tight, particularly for a large number of relay station antennas. These closed-form expressions enable us to determine the regions where the full-duplex mode outperforms the half-duplex mode, as well as to design an optimal power allocation scheme. This optimal power allocation scheme aims to maximize the energy efficiency for a given sum spectral efficiency and under peak power constraints at the relay station and sources. Numerical results verify the effectiveness of the optimal power allocation scheme. Furthermore, we show that, by doubling the number of transmit/receive antennas at the relay station, the transmit power of each source and of the relay station can be reduced by 1.5 dB if the pilot power is equal to the signal power, and by 3 dB if the pilot power is kept fixed, while maintaining a given quality of service.

zero-forcing (ZF)

full-duplex

massive MIMO

Decode-and-forward relay channel

maximum-ratio combining (MRC)

maximum-ratio transmission (MRT)

Author

H. Q. Ngo

Linköping University

H. A. Suraweera

University of Peradeniya

Michail Matthaiou

Chalmers, Signals and Systems, Signal Processing and Biomedical Engineering

E. G. Larsson

Linköping University

IEEE Journal on Selected Areas in Communications

0733-8716 (ISSN) 15580008 (eISSN)

Vol. 32 9 1721-1737 6832435

Subject Categories

Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1109/jsac.2014.2330091

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