
Robust secure transmission for wireless information and power transfer in heterogeneous networks
Author(s) -
Kaizhi Huang,
Bo Zhang
Publication year - 2019
Publication title -
iet communications
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.355
H-Index - 62
eISSN - 1751-8636
pISSN - 1751-8628
DOI - 10.1049/iet-com.2018.5529
Subject(s) - macrocell , artificial noise , computer science , beamforming , transmission (telecommunications) , base station , femtocell , wireless , telecommunications link , transmitter power output , mathematical optimization , maximum power transfer theorem , computer network , power (physics) , telecommunications , transmitter , mathematics , physical layer , channel (broadcasting) , physics , quantum mechanics
Here, the authors investigate robust secure transmission for wireless information and power transfer in heterogeneous networks (HeNets) under the deterministic and stochastic CSI errors, respectively, where one macrocell base station (MBS) and one femtocell base station (FBS) respectively serve to macrocell users (MUs) and femtocell users (FUs). Meanwhile, FUs acquire energy from the FBS and multiple eavesdroppers attempt to wiretap its downlink information. To secure the wireless information and power transfer, the authors propose an artificial noise (AN)‐aided transmission design. Under the deterministic CSI error, the authors jointly design the beamforming and AN vectors of the MBS and FBS to minimise the total transmit power, while satisfying the constraints on the signal‐to‐interference plus noise (SINR) requirement at each MU, energy harvesting (EH) and secrecy outage probability requirement at each FU. This formulated problem is non‐convex. Utilising S‐procedure and successive convex approximation technique, the authors successfully transfer it into a series of convex problems. Under the stochastic CSI error, the joint design problem is formulated with a range of outage probabilistic constraints. Further, the authors, respectively, resort to large deviation and Bernstein‐type inequalities, S‐procedure to convert it into solvable forms. Simulation results demonstrate the effectiveness of the authors’ proposed design.