TY - JOUR
T1 - Resource allocation for physical layer security in heterogeneous network with hidden eavesdropper
AU - Gong, Shiqi
AU - Xing, Chengwen
AU - Fei, Zesong
AU - Kuang, Jingming
N1 - Publisher Copyright:
© 2013 IEEE.
PY - 2016/3
Y1 - 2016/3
N2 - The tremendous performance gain of heterogeneous networks (HetNets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for HetNets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker (KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.
AB - The tremendous performance gain of heterogeneous networks (HetNets) is at the cost of complicated resource allocation. Considering information security, the resource allocation for HetNets becomes much more challenging and this is the focus of this paper. In this paper, the eavesdropper is hidden from the macro base stations. To relax the unpractical assumption on the channel state information on eavesdropper, a localization based algorithm is first given. Then a joint resource allocation algorithm is proposed in our work, which simultaneously considers physical layer security, cross-tier interference and joint optimization of power and subcarriers under fairness requirements. It is revealed in our work that the considered optimization problem can be efficiently solved relying on convex optimization theory and the Lagrangian dual decomposition method is exploited to solve the considered problem effectively. Moreover, in each iteration the closed-form optimal resource allocation solutions can be obtained based on the Karush-Kuhn-Tucker (KKT) conditions. Finally, the simulation results are given to show the performance advantages of the proposed algorithm.
KW - Lagrangian dual decomposition
KW - RSS-based location estimation
KW - heterogeneous networks
KW - physical layer security
KW - resource allocation
UR - http://www.scopus.com/inward/record.url?scp=84963818586&partnerID=8YFLogxK
U2 - 10.1109/CC.2016.7445504
DO - 10.1109/CC.2016.7445504
M3 - Article
AN - SCOPUS:84963818586
SN - 1673-5447
VL - 13
SP - 82
EP - 95
JO - China Communications
JF - China Communications
IS - 3
M1 - 7445504
ER -