Artificial Noise Assisted Secure Interference Networks With Wireless Power Transfer

作者：Zhao, Nan; Cao, Yang; Yu, F. Richard; Chen, Yunfei; Jin, Minglu^*; Leung, Victor C. M.

来源：IEEE Transactions on Vehicular Technology, 2018, 67(2): 1087-1098.

DOI：10.1109/TVT.2017.2700475

• Artificial noise
• interference alignment
• passive eavesdropping
• physical layer security
• wireless power transfer

Interference alignment (IA) is a remarkable technique to manage interference, and artificial noise (AN) can be utilized to combat one main threat of security, passive eavesdropping. Nevertheless, in the existing schemes, AN is only eliminated at each legitimate receiver, which is a waste of energy. In this paper, we propose an AN-assisted IA scheme with wireless power transfer. In the proposed scheme, AN is generated by each transmitter along with data streams, which can disrupt the eavesdropping without introducing any additional interference. Due to the fact that the transmit power of AN should be high enough to ensure the security, energy harvesting (EH) is also performed in the scheme. A power splitter is equipped at each receiver, which can divide the received signal, including desired signal, interference and AN, into two parts: one for information decoding and the other for EH. To optimize the antieavesdropping performance, the total transmit power of AN is maximized by jointly optimizing the information transmit power and the coefficient of power splitting, with the requirements of signal-to-interference-plus-noise ratio and harvested power satisfied. Due to the nonconvex nature of the problem, a suboptimal solution is also derived to calculate the closed-form solutions with extremely low computational complexity. Extensive simulation results are presented to show the effectiveness of the proposed scheme.

• 出版日期2018-2
• 单位大连理工大学