Secure User-Centric Clustering for Energy Efficient Ultra-Dense Networks: Design and Optimization

With an unprecedented amount of sensitive private data generated by mobile user equipment (UE), securing the emerging ultra-dense networks (UDNs) becomes critical. Although involving more access points (APs) is potentially capable of enhancing both the UE's throughput and security, the energy c...

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Bibliographic Details
Published in:IEEE journal on selected areas in communications Vol. 36; no. 7; pp. 1609 - 1621
Main Authors: Lin, Yan, Zhang, Rong, Yang, Luxi, Hanzo, Lajos
Format: Journal Article
Language:English
Published: New York IEEE 01.07.2018
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Clustering
Design optimization
Eavesdropping
Energy consumption
Energy efficiency
Energy transmission
Greedy algorithms
Jamming
Linear programming
Mixed integer
Nonlinear programming
Numerical models
Optimization
physical layer security
Power efficiency
Quality of service
Secrecy aspects
secrecy energy efficiency
secure user-centric clustering
Security
Throughput
UDN
Wireless communication
ISSN:0733-8716, 1558-0008
Online Access:Get full text
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Summary:With an unprecedented amount of sensitive private data generated by mobile user equipment (UE), securing the emerging ultra-dense networks (UDNs) becomes critical. Although involving more access points (APs) is potentially capable of enhancing both the UE's throughput and security, the energy consumption becomes significant. In this paper, we investigate secure UDNs in the context of the user-centric clustering of UDNs from a secrecy energy efficiency perspective, while satisfying both the throughput and the security of each UE. We first propose a secure user-centric clustering architecture by introducing both a dedicated jamming strategy and an embedded jamming strategy, both of which degrade the overheard signals of the eavesdroppers and guarantee secure transmission relying on the different APs' involvement status. We formulate the secure user-centric clustering design for both known and unknown eavesdropper channel state information (CSI), whilst maximizing the secrecy energy efficiency with the aid of various secure transmission schemes. Since the problem formulated is a non-convex mixed integer non-linear programming problem, we develop a set of heuristic greedy secure user-centric clustering algorithms for diverse operating scenarios. Finally, our numerical results reveal the quantitative benefits of the proposed secure user-centric clustering architectures as a function of the network densities (i.e., AP, UE, and eavesdropper) and of both the throughput and the security constraints on the secrecy energy efficiency trade-off in different scenarios.
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ISSN:0733-8716
1558-0008
DOI:10.1109/JSAC.2018.2825178