Energy Efficiency of Confidential Multi-Antenna Systems With Artificial Noise and Statistical CSI

The problem of energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. The use of artificial noise (AN) in combination with different statistical channel state information s...

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Bibliographic Details
Published in:IEEE journal of selected topics in signal processing 2016-12, Vol.10 (8), p.1462-1477
Main Authors: Zappone, Alessio, Pin-Hsun Lin, Jorswieck, Eduard
Format: Article
Language:English
Subjects:
Algorithms
Antennas
Artificial noise
Channel estimation
Channel state information
Computational geometry
Convexity
Digital signal processing
Digital signal processors
Eavesdropping
Energy consumption
Energy efficiency
fractional programming
Maximization
Microprocessors
MIMO
MISO-SE
Optimization
Physical layer
physical layer security
Polynomials
Power consumption
Power control
Reliability
Resource allocation
Resource management
Signal processing
statistical CSI
Wiretapping
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Summary:The problem of energy-efficient resource allocation in multiple-antenna wiretap channels is investigated, wherein a malicious user tries to eavesdrop the communication between two legitimate users. The use of artificial noise (AN) in combination with different statistical channel state information scenarios at the legitimate transmitter is considered. Unlike most previous related papers, the goal of the resource allocation is to maximize the amount of bits which can be reliably and confidentially transmitted per Joule of consumed energy. This leads to the maximization of the ratio between the system secrecy capacity and consumed power, a metric which we label secrecy energy efficiency (SEE). The resulting nonconvex maximization problems are tackled by means of the fractional programing and sequential convex optimization tools. The resulting algorithm monotonically increases the objective value, and upon convergence, yields a first-order optimal solution of the problem with a polynomial complexity. Moreover, the impact of using the AN technique on the energy consumption due to digital signal processing operations is explicitly accounted for, providing insight as to when AN is beneficial from an energy-efficient perspective, too. Numerical results show the merits of the proposed algorithms, also showing that AN does not always improve the system SEE, depending on the digital signal processor used to compute the resource allocation.
ISSN:1932-4553
1941-0484
DOI:10.1109/JSTSP.2016.2607690