AuthorsL. Jiang, H. Tian, J. Shen, S. Maharjan and Y. Zhang
TitleQuality of Protection in Cloud-Assisted Cognitive Machine-to-Machine Communications for Industrial Systems
AfilliationCommunication Systems
Project(s)The Center for Resilient Networks and Applications
Publication TypeJournal Article
Year of Publication2016
JournalACM/Springer Mobile Networks and Applications

Cloud-assisted cognitive machine-to-machine communications (CM2M) is a new paradigm to improve the mobile services, which have drawn considerable attention in industry and academia. In this paper, we consider the quality of protection (QoP) of information transmission in cloud-assisted CM2M communications. In such an environment, the secondary M2M system intends to share the primary spectrum on the condition that the secondary transmitter (ST) has to relay the primary message. However, the ST is a low-energy device which adopts the energy harvesting technique to power itself. In particular, we focus on secure information transmission for the primary system when the secondary users (SUs) are the potential eavesdroppers. We aim to jointly design power splitting and secure beamforming to maximize the secondary M2M system data rate subject to the secrecy requirement of the primary system and the ST power constraint. To solve this non-convex problem, we propose a computationally efficient two-stage optimization approach. Simulation results demonstrate that our proposed scheme achieves a significant transmission rate of the secondary M2M system while provides a high secrecy rate for the primary system compared to the scheme without energy harvesting.

Citation Key24766