  In this paper, we study the secrecy throughput of a full-duplex wireless
powered communication network (WPCN) for internet of things (IoT). The WPCN
consists of a full-duplex multi-antenna base station (BS) and a number of
sensor nodes. The BS transmits energy all the time, and each node harvests
energy prior to its transmission time slot. The nodes sequentially transmit
their confidential information to the BS, and the other nodes are considered as
potential eavesdroppers. We first formulate the sum secrecy throughput
optimization problem of all the nodes. The optimization variables are the
duration of the time slots and the BS beamforming vectors in different time
slots. The problem is shown to be non-convex. To tackle the problem, we propose
a suboptimal two stage approach, referred to as sum secrecy throughput
maximization (SSTM). In the first stage, the BS focuses its beamforming to
blind the potential eavesdroppers (other nodes) during information transmission
time slots. Then, the optimal beamforming vector in the initial non-information
transmission time slot and the optimal time slots are derived. We then consider
fairness among the nodes and propose max-min fair (MMF) and proportional fair
(PLF) algorithms. The MMF algorithm maximizes the minimum secrecy throughput of
the nodes, while the PLF tries to achieve a good trade-off between the sum
secrecy throughput and fairness among the nodes. Through numerical simulations,
we first demonstrate the superior performance of the SSTM to uniform time
slotting and beamforming in different settings. Then, we show the effectiveness
of the proposed fair algorithms.
