UAV Swarm-Enabled Aerial CoMP: A Physical Layer Security Perspective

Unlike aerial base station enabled by a single unmanned aerial vehicle (UAV), aerial coordinated multiple points (CoMP) can be enabled by a UAV swarm. In this case, the management of multiple UAVs is important. This paper considers the power allocation strategy for a UAV swarm-enabled aerial network to enhance the physical layer security of the downlink transmission, where an eavesdropper moves following the trajectory of the swarm for better eavesdropping. Unlike existing works, we use only the large-scale channel state information (CSI) and maximize the secrecy throughput in a whole-trajectory-oriented manner. The overall transmission energy constraint on each UAV and the total transmission duration for all the legitimate users are considered. The non-convexity of the formulated problem is solved by using max-min optimization with iteration. Both the transmission power of desired signals and artificial noise (AN) are derived iteratively. Simulation results are presented to validate the effectiveness of our proposed power allocation algorithm and to show the advantage of aerial CoMP by using only the large-scale CSI

Revisit assignments of the new excited Ωc\Omega_c states with QCD sum rules

In this article, we distinguish the contributions of the positive parity and negative parity $\Omega_c$ states, study the masses and pole residues of the 1S, 1P, 2S and 2P $\Omega_c$ states with the spin $J=\frac{1}{2}$ and $\frac{3}{2}$ using the QCD sum rules in a consistent way, and revisit the assignments of the new narrow excited $\Omega_c^0$ states. The predictions support assigning the $\Omega_c(3000)$ to be the 1P $\Omega_c$ state with $J^P={\frac{1}{2}}^-$, assigning the $\Omega_c(3090)$ to be the 1P $\Omega_c$ state with $J^P={\frac{3}{2}}^-$ or the 2S $\Omega_c$ state with $J^P={\frac{1}{2}}^+$, and assigning $\Omega_c(3119)$ to be the 2S $\Omega_c$ state with $J^P={\frac{3}{2}}^+$.Comment: 19 pages, 22 figures. arXiv admin note: text overlap with arXiv:1705.0774

Hybrid Satellite-Terrestrial Communication Networks for the Maritime Internet of Things: Key Technologies, Opportunities, and Challenges

With the rapid development of marine activities, there has been an increasing number of maritime mobile terminals, as well as a growing demand for high-speed and ultra-reliable maritime communications to keep them connected. Traditionally, the maritime Internet of Things (IoT) is enabled by maritime satellites. However, satellites are seriously restricted by their high latency and relatively low data rate. As an alternative, shore & island-based base stations (BSs) can be built to extend the coverage of terrestrial networks using fourth-generation (4G), fifth-generation (5G), and beyond 5G services. Unmanned aerial vehicles can also be exploited to serve as aerial maritime BSs. Despite of all these approaches, there are still open issues for an efficient maritime communication network (MCN). For example, due to the complicated electromagnetic propagation environment, the limited geometrically available BS sites, and rigorous service demands from mission-critical applications, conventional communication and networking theories and methods should be tailored for maritime scenarios. Towards this end, we provide a survey on the demand for maritime communications, the state-of-the-art MCNs, and key technologies for enhancing transmission efficiency, extending network coverage, and provisioning maritime-specific services. Future challenges in developing an environment-aware, service-driven, and integrated satellite-air-ground MCN to be smart enough to utilize external auxiliary information, e.g., sea state and atmosphere conditions, are also discussed