Approximate Secrecy Capacity of Gaussian Parallel Relay Networks

We consider a Gaussian relay network, which has to protect the message from a powerful eavesdropper, which has the possibility of listening to the transmitted signals on orthogonal channels. The secrecy capacity of the Gaussian network is approximated by considering the corresponding network in the...

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Bibliographic Details
Published in:IEEE transactions on information theory Vol. 61; no. 10; pp. 5525 - 5534
Main Authors: Schrammar, Nicolas, Skoglund, Mikael
Format: Journal Article
Language:English
Published: New York IEEE 01.10.2015
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Approximation
Approximation methods
AWGN channels
Channel capacity
Channel models
communication networks
Communication system security
Communications networks
Data integrity
Electronic surveillance
Normal distribution
Relay networks (telecommunications)
Topology
Wireless communication
AWGN channels
channel models
communication networks
channel capacity
communication system security
ISSN:0018-9448, 1557-9654, 1557-9654
Online Access:Get full text
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Summary:We consider a Gaussian relay network, which has to protect the message from a powerful eavesdropper, which has the possibility of listening to the transmitted signals on orthogonal channels. The secrecy capacity of the Gaussian network is approximated by considering the corresponding network in the deterministic discrete superposition model. Upper and lower bounds on the secrecy capacity are found in terms of the deterministic model, which are potentially easier to evaluate. We perform this evaluation for the particular topology of the parallel relay network, where the relays form a parallel layer between the source and the destination. By analyzing the deterministic model, we approximate the secrecy capacity within a constant gap. The approximation can be expressed just in terms of the channel gains of the network. It is therefore possible to deduct that the simple scheme of hiding the transmitted signals in noise is approximately optimal.
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ISSN:0018-9448
1557-9654
1557-9654
DOI:10.1109/TIT.2015.2468216