Facing to jammers and eavesdroppers, conventional security data transmission is generally based on the cryptographic method. Enormous issues arise when the cryptographic method applied in dynamic wireless scenarios, such as key distribution for symmetric cryptosystems, and high computing complexity of asymmetric cryptosystems. With the rapid growing of wireless traffic and massive device accessing of Internet-of-Things (IoT), the computing complexity and energy consumption aggravate, which leads to security degrade of wireless networks. To address this issue, a secure communication scheme based on physical layer security was proposed for Full-Duplex (FD) wireless-powered IoT networks, which limited the amount of information received at the unauthorized receiver by exploiting the randomness of noise and wireless channel. In this method, secrecy capacity was analyzed based on information theory, and then the Secrecy Outage Probability (SOP) was derived with the analysis model of secrecy capacity. In addition, considering the influence of noise, jammer interference, spatial mutual interference, and residual self-interference on safety capacity, a secure beamforming method was proposed to increase the mutual information between the transmitting and receiving ends and improve the secrecy capacity of the full-duplex wireless-powered IoT network by decreasing the joint interference. Derivation results are verified through Monte Carlo simulation. Simulation results show that the FD wireless-powered IoT with secure beamforming is superior to the conventional wireless-powered IoT in terms of secrecy capacity and SOP.

Slot-ALOHA is widely used in wireless communications due to its simplicity. However, because slot-ALOHA is not stable in essence, many algorithms have been used to provide steady throughput. After founding the Markov model for Binary Exponent Backoff (BEB) algorithm, this paper analyzed the adjusting progress. The numerical computation and simulation results demonstrate that BEB algorithm can guarantee the system steady and the theoretic throughput can be derived when the number of modes is within certain range. By comparing throughput of BEB to that of Pseudo-Bayesian Control Algorithm (PBCA), it can derive that the throughput of BEB is less than PBCA when the number of users is either too big or small because of being influenced by the backoff window size.