Securing UAV Communications Via Trajectory Optimization

Unmanned aerial vehicle (UAV) communications has drawn significant interest recently due to many advantages such as low cost, high mobility, and on-demand deployment. This paper addresses the issue of physical-layer security in a UAV communication system, where a UAV sends confidential information to a legitimate receiver in the presence of a potential eavesdropper which are both on the ground. We aim to maximize the secrecy rate of the system by jointly optimizing the UAV's trajectory and transmit power over a finite horizon. In contrast to the existing literature on wireless security with static nodes, we exploit the mobility of the UAV in this paper to enhance the secrecy rate via a new trajectory design. Although the formulated problem is non-convex and challenging to solve, we propose an iterative algorithm to solve the problem efficiently, based on the block coordinate descent and successive convex optimization methods. Specifically, the UAV's transmit power and trajectory are each optimized with the other fixed in an alternating manner until convergence. Numerical results show that the proposed algorithm significantly improves the secrecy rate of the UAV communication system, as compared to benchmark schemes without transmit power control or trajectory optimization.Comment: Accepted by IEEE GLOBECOM 201

Robust optimal dispatching model and a benefit allocation strategy for rural novel virtual power plants incorporating biomass waste energy conversion and carbon cycle utilization

To optimize the utilization of rural biomass waste resources (e.g., straw and solid waste), biomass waste energy conversion (BWEC) and carbon cycle utilization (CCU) are integrated into a traditional virtual power plant, i.e., a rural BWEC-CCU-based virtual power plant. Furthermore, a fuzzy robust two-stage dispatching optimal model for the BWEC-CCU-based virtual power plant is established considering the non-determinacy from a wind power plant (WPP) and photovoltaic (PV) power. The scheduling model includes the day-ahead deterministic dispatching model and real-time uncertainty dispatching model. Among them, in the day-ahead dispatching phase, the dispatching plan is formulated with minimum operating cost and carbon emission targets. In the real-time dispatching phase, the optimal dispatching strategy is formulated aiming at minimum deviation adjustment cost by applying the Latin hypercube sampling method. The robust stochastic theory is used to describe the uncertainty. Third, in order to achieve optimal distribution of multi-agent cooperation benefits, a benefit distribution strategy based on Nash negotiation is designed considering the three-dimensional interfering factor of the marginal benefit contribution, carbon emission contribution, and deviation risk. Finally, a rural distribution network in Jiangsu province, China, is selected for case analysis, and the results show that 1) the synergistic optimal effect of BWEC and CCU is obvious, and the operation cost and deviation adjustment cost could decrease by 26.21% and 39.78%, respectively. While the capacity ratio of WPP + PV, BWEC, and CCU is 5:3:2, the dispatching scheme is optimum. 2) This scheduling model can be used to formulate the optimal scheduling scheme. Compared with the robust coefficient Γ = 0, when Γ = 1, the WPP and PV output decreased by 15.72% and 15.12%, and the output of BWEC and CCU increased by 30.7% and 188.19%, respectively. When Γ∈ (0.3, 0.9), the growth of Γ has the most direct impact on the dispatching scheme. 3) The proposed benefit equilibrium allocation strategy can formulate the most reasonable benefit allocation plan. Compared with the traditional benefit allocation strategy, when the proposed method is used, the benefit share of the WPP and PV reduces by 5.2%, and the benefit share of a small hydropower station, BWEC, and CCU increases by 1.7%, 9.7%, and 3.8%, respectively. Overall, the proposed optimal dispatching and benefit allocation strategy could improve the aggregated utilization of rural biomass waste resources and distributed energy resources while balancing the benefit appeal of different agents

Rescue of HLH with T and B Lymphocyte Involvement Due to Epstein-Barr Virus by PD-1 Inhibitor/Ruxolitinib and Rituximab Combination Regimens: A Case Report

Hemophagocytic lymphohistiocytosis (HLH) is a fatal clinical syndrome. The most common cause of secondary HLH is Epstein-Barr virus (EBV) infection. EBV-HLH is a common clinical disease with high mortality, easy relapse, and poor prognosis. Therefore, treating EBV-HLH with T and B lymphocyte involvement is challenging, and selecting an appropriate treatment regimen is critical. Moreover, research on how to evaluate the recurrence index after remission is scarce. In this study, we reported a case of EBV-HLH successfully treated with programmed cell death protein-1 (PD-1) inhibitor in combination with rituximab. The regimen had a good curative effect, and we successfully detected the trend of early recurrence. Our findings indicated that PD-1 inhibitor in combination with rituximab may help to treat EBV-HLH and maintain EBV-infected T and B whole-line lymphocytes