Secure 5G Wireless Communications: A Joint Relay Selection and Wireless Power Transfer Approach

In this paper, we investigate the secrecy performance of an energy harvesting relay system, where a legitimate source communicates with a legitimate destination via the assistance of multiple trusted relays. In the considered system, the source and relays deploy the time-switching-based radio frequency energy harvesting technique to harvest energy from a multi-antenna beacon. Different antenna selection and relay selection schemes are applied to enhance the security of the system. Specifically, two relay selection schemes based on the partial and full knowledge of channel state information, i.e., optimal relay selection and partial relay selection, and two antenna selection schemes for harvesting energy at source and relays, i.e., maximizing energy harvesting channel for the source and maximizing energy harvesting channel for the selected relay, are proposed. The exact and asymptotic expressions of secrecy outage probability in these schemes are derived. We demonstrate that applying relay selection approaches in the considered energy harvesting system can enhance the security performance. In particular, optimal relay selection scheme outperforms partial relay selection scheme and achieves full secrecy diversity order, regardless of energy harvesting scenarios.

Integrated Optimal Power Flow for Distribution Networks in Local and Urban Scales

This paper develops an integrated optimal power flow (OPF) tool for distribution networks in two spatial scales. In the local scale, the distribution network, the natural gas network, and the heat system are coordinated as a microgrid. In the urban scale, the impact of natural gas network is considered as constraints for the distribution network operation. The proposed approach incorporates unbalance three-phase electrical systems, natural gas systems, and combined cooling, heating, and power systems. The interactions among the above three energy systems are described by energy hub model combined with components capacity constraints. In order to efficiently accommodate the nonlinear constraint optimization problem, particle swarm optimization algorithm is employed to set the control variables in the OPF problem. Numerical studies indicate that by using the OPF method, the distribution network can be economically operated. Also, the tie-line power can be effectively managed.