Visible to the public Biblio

Filters: Author is Gao, H.  [Clear All Filters]
2017-12-27
Wang, Y., Kang, S., Lan, C., Liang, Y., Zhu, J., Gao, H..  2016.  A five-dimensional chaotic system with a large parameter range and the circuit implementation of a time-switched system. 2016 11th International Conference on Reliability, Maintainability and Safety (ICRMS). :1–6.

To enhance the encryption and anti-translation capability of the information, we constructed a five-dimensional chaotic system. Combined with the Lü system, a time-switched system with multiple chaotic attractors is realized in the form of a digital circuit. Some characteristics of the five-dimensional system are analyzed, such as Poincare mapping, the Lyapunov exponent spectrum, and bifurcation diagram. The analysis shows that the system exhibits chaotic characteristics for a wide range of parameter values. We constructed a time-switched expression between multiple chaotic attractors using the communication between a microcontroller unit (MCU) and field programmable gate array (FPGA). The system can quickly switch between different chaotic attractors within the chaotic system and between chaotic systems at any time, leading to signal sources with more variability, diversity, and complexity for chaotic encryption.

2019-02-08
Cao, R., Wong, T. F., Gao, H., Wang, D., Lu, Y..  2018.  Blind Channel Direction Separation Against Pilot Spoofing Attack in Massive MIMO System. 2018 26th European Signal Processing Conference (EUSIPCO). :2559-2563.

This paper considers a pilot spoofing attack scenario in a massive MIMO system. A malicious user tries to disturb the channel estimation process by sending interference symbols to the base-station (BS) via the uplink. Another legitimate user counters by sending random symbols. The BS does not possess any partial channel state information (CSI) and distribution of symbols sent by malicious user a priori. For such scenario, this paper aims to separate the channel directions from the legitimate and malicious users to the BS, respectively. A blind channel separation algorithm based on estimating the characteristic function of the distribution of the signal space vector is proposed. Simulation results show that the proposed algorithm provides good channel separation performance in a typical massive MIMO system.