4.8 Article

Device-Centric Distributed Antenna Transmission: Secure Precoding and Antenna Selection With Interference Exploitation

Journal

IEEE INTERNET OF THINGS JOURNAL
Volume 7, Issue 3, Pages 2293-2308

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JIOT.2019.2958420

Keywords

Power demand; Interference; Signal to noise ratio; Precoding; Robustness; Security; Active matrix addressing; Antenna selection; constructive artificial noise (AN); distributed antenna (DA); robust optimization; secure precoding

Funding

  1. Engineering and Physical Sciences Research Council, U.K. [EP/R007934/1]
  2. EPSRC [EP/R007934/1] Funding Source: UKRI

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In this article, we address physical layer security in the distributed antenna (DA) systems, where eavesdroppers (Eves) can intercept the information transmitted for the intended receiver (IR). To realize a device-centric, power-efficient, and physical-layer security-aware system, we aim at minimizing power consumption by jointly designing DA selection and secure precoding. Different from the conventional artificial noise (AN)-aided secure transmission, where AN is treated as an undesired element for the IR, we design AN such that it is constructive to the IR while keeping destructive to the Eves. Importantly, we investigate two practical scenarios, where the IR and Eves' channel state information (CSI) are imperfectly obtained or the Eves' CSI is completely unknown. To handle the CSI uncertainties, we solve the problems in probabilistic and deterministic robust optimizations, respectively, both satisfying the IR' signal-to-interference-plus-noise ratio (SINR) requirement by the use of constructive AN and addressing security against the Eves. The simulation results demonstrate our algorithms consume much less power compared to the centralized antenna (CA) systems with/without antenna selection, as well as the DA systems with conventional AN processing. Last but not least, by the proposed algorithms, the activation of DAs closely relates to devices' locations and quality-of-service (QoS) requirements, featuring a device-centric and on-demand structure.

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