Generative Adversarial Learning for Intelligent Trust Management in 6G Wireless Networks

Emerging six generation (6G) is the integration of heterogeneous wireless networks, which can seamlessly support anywhere and anytime networking. But high Quality-of-Trust should be offered by 6G to meet mobile user expectations. Artificial intelligence (AI) is considered as one of the most important components in 6G. Then AI-based trust management is a promising paradigm to provide trusted and reliable services. In this article, a generative adversarial learning-enabled trust management method is presented for 6G wireless networks. Some typical AI-based trust management schemes are first reviewed, and then a potential heterogeneous and intelligent 6G architecture is introduced. Next, the integration of AI and trust management is developed to optimize the intelligence and security. Finally, the presented AI-based trust management method is applied to secure clustering to achieve reliable and real-time communications. Simulation results have demonstrated its excellent performance in guaranteeing network security and service quality

Extended ammonia observations towards the 'Integral-Shaped Filament'

Recent observations suggest a scenario in which filamentary structures in the ISM represent the first step towards clumps/cores and eventually star formation. The densest filaments would then fragment into prestellar cores owing to gravitational instability. We seek to understand the roles filamentary structures play in high-mass star formation. We mapped the integral-shaped filament (ISF) in NH3 (1, 1) and (2, 2). The whole filamentary structure is uniformly and fully sampled. We find that the morphology revealed by the map of velocity-integrated intensity of the NH3 (1, 1) line is closely associated with the dust ridge. We identify 6 "clumps" related to the well known OMC-1 to 5 and 11 "sub-clumps" within the map and they are separated not randomly but in roughly equal intervals along the ISF. The average spacing of clumps is 11.30'$\pm$1.31' (1.36$\pm$0.16 pc ) and the average spacing of sub-clumps is 7.18'$\pm$1.19' (0.86$\pm$0.14 pc). These spacings agree well with the predicted values of the thermal (0.86 pc) and turbulent sausage instability (1.43 pc) by adopting a cylindric geometry of the ISF with an inclination of $60^{\circ}$ with respect to the line of sight. We also find a velocity gradient of about 0.6 km s-1 pc-1 that runs along the ISF which likely arises from an overall rotation of the Orion A molecular cloud. The inferred ratio between rotational and gravitational energy is well below unity. Furthermore, fluctuations are seen in the centroid velocity diagram along the ISF. The OMC-1 to 5 clouds are located close to the local extrema of the fluctuations, which suggests that there exist gas flows associated with these clumps in the ISF. The derived NH3 (1, 1) and (2, 2) rotation temperatures in the OMC-1 are about 30-40 K. In OMC-2, OMC-3, and the northern part of OMC-4, we find higher and lower temperatures at the boundaries and in the interior, respectively.Comment: Accepted by A&A. 14 pages, 14 figure