Secure Massive MIMO Systems With Limited RF Chains

In future practical deployments of massive multi-input multi-output (MIMO) systems, the number of radio-frequency (RF) chains at the base stations (BSs) may be much smaller than the number of BS antennas to reduce the overall expenditure. In this correspondence, we propose a novel design framework f...

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Veröffentlicht in:IEEE transactions on vehicular technology Jg. 66; H. 6; S. 5455 - 5460
Hauptverfasser: Zhu, Jun, Xu, Wei, Wang, Ning
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.06.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Antenna arrays
Artificial noise
Baseband
Chains
Cybersecurity
Downlink
hybrid precoder
imperfect channel-state information (CSI)
limited radio-frequency (RF) chains
Lower bounds
massive multiple-input multiple-output (MIMO)
MIMO
MIMO (control systems)
physical layer security
Precoding
Radio equipment
Radio frequency
Security
ISSN:0018-9545, 1939-9359
Online-Zugang:Volltext
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Zusammenfassung:In future practical deployments of massive multi-input multi-output (MIMO) systems, the number of radio-frequency (RF) chains at the base stations (BSs) may be much smaller than the number of BS antennas to reduce the overall expenditure. In this correspondence, we propose a novel design framework for joint data and artificial noise (AN) precoding in a multiuser massive MIMO system with limited number of RF chains, which improves the wireless security performance. With imperfect channel state information (CSI), we analytically derive an achievable lower bound on the ergodic secrecy rate of any mobile terminal (MT) for both analog and hybrid precoding schemes. The closed-form lower bound is used to determine optimal power splitting between data and AN that maximizes the secrecy rate through simple 1-D search. Analytical and numerical results together reveal that the proposed hybrid precoder, although suffering from reduced secrecy rate compared with the theoretical full-dimensional precoder, is free of the high computational complexity of large-scale matrix inversion and null-space calculations and largely reduces the hardware cost.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2016.2615885