Channel Knowledge Map(CKM)-Assisted Multi-UAV Wireless Network:CKM Construction and UAV Placement

Channel knowledge map(CKM)has recently emerged as a viable new solution to facilitate the placement and trajectory optimization for unmanned aerial vehicle(UAV)communications,by exploiting the siteand location-specific radio propagation information.This paper investigates a CKM-assisted multi-UAV wireless network,by focusing on the construction and utilization of CKMs for multi-UAV placement optimization.First,we consider the CKM construction problem when data measurements for only a limited number of points are available.Towards this end,we exploit a data-driven interpolation technique,namely the Kriging method,to construct CKMs to characterize the signal propagation environments.Next,we study the multi-UAV placement optimization problem by utilizing the constructed CKMs,in which the multiple UAVs aim to optimize their placement locations to maximize the weighted sum rate with their respectively associated ground base stations(GBSs).However,the weighted sum rate function based on the CKMs is generally non-differentiable,which renders the conventional optimization techniques relying on function derivatives inapplicable.To tackle this issue,we propose a novel iterative algorithm based on derivative-free optimization,in which a series of quadratic functions are iteratively constructed to approximate the objective function under a set of interpolation conditions,and accordingly,the UAVs’placement locations are updated by maximizing the approximate function subject to a trust region constraint.Finally,numerical results are presented to validate the performance of the proposed designs.It is shown that the Kriging method can construct accurate CKMs for UAVs.Furthermore,the proposed derivative-free placement optimization design based on the Kriging-constructed CKMs achieves a weighted sum rate that is close to the optimal exhaustive search design based on ground-truth CKMs,but with much lower implementation complexity.In addition,the proposed design is shown to significantly outperform other benchmark schemes.

Spectrum Usage Anomaly Detection from Sub-Sampled Data Stream via Deep Neural Network

Anomaly detection is an essential part of any practical system in order to remedy any malfunction and accident early to create a secure and robust system.Malicious users and malfunctioning cognitive radio(CR)devices may cause severe interference to legitimate users.However,there are no effective methods to detect spontaneous and irregular anomaly behaviors in sub-sampling data stream from wideband compressive spectrum sensing as an important function of a CR device.In this article,to detect anomaly utilization of spectrum from sub-sampled data stream,a multiple layer perceptron/feed-forward neural network(FFNN)based solution is proposed.The proposed solution would learn the pattern of legitimate and anomalous usages autonomously without expert's knowledge.The proposed neural network(NN)framework has also shown benefits such as more than 80%faster detection speed and lower detection error rate.

Online search for UAV relay placement for free-space optical communication under shadowing

Unmanned aerial vehicle(UAV)relaying is promising to overcome the challenge of signal blockage in free-space optical(FSO)communications for users in dense urban area.Existing works on UAV relay placement are mostly based on simplified line-of-sight(LOS)channel models or probabilistic channel models,and thus fail to capture the actual LOS status of the optical communication link.By contrast,this paper studies three-dimensional(3D)online placement for a UAV to construct relay links to two ground users in deep shadow with LOS guarantees.By analyzing the properties of the UAV relay placement problem,it is found that searching on a plane that approximates the equipotential surface can achieve a good performance and complexity trade-off for a good placement of the UAV relay in 3D.Based on these insights,a two-stage online search algorithm on an equipotential plane(TOSEP)is developed for a special case where the equipotential surface turns out to be an equipotential plane.For the general case,a strategy called gradient projected online search algorithm on an approximated equipotential plane(GOSAEP)is developed,which approximates the equipotential surface with a perpendicular plane using the gradient projection method.Numerical experiments are conducted over a real-world city topology,and it is shown that the GOSAEP achieves over 95%of the performance of the exhaustive 3D search scheme within a 300-m search length.

m^(6)A-mediated regulation of PBX1-GCH1 axis promotes gastric cancer proliferation and metastasis by elevating tetrahydrobiopterin levels

Background:Methyltransferase 3(METTL3)-mediated N6-methyladenosine(m^(6)A)RNA modification has been demonstrated to be a potential factor in promoting gastric cancer(GC).METTL3 regulates a series of signaling pathways by modifying various mRNAs.This study aimed to identify novel METTL3-mediated signaling pathways and explored possible targets for use in the clinical setting of gastric cancer.Methods:To investigate the proliferation and metastatic capacity ofGCcell lines with METTL3 knockdown,a xenograft,lung metastasis,and popliteal lymph node metastasis model was used.Them^(6)A-modified RNA immunoprecipitation(Me-RIP)sequence was utilized to explore the target mRNAs of METTL3.Cell counting kit 8 and transwell assays were performed to investigate the promoting function of pre-B cell leukemia homeobox 1(PBX1)and GTP cyclohydrolase 1(GCH1).Western blotting and chromatin immunoprecipitation were employed to confirm the involvement of the METTL3-PBX1-GCH1 axis.ELISA and liquid chromatography-mass spectrometry were used to explore the biological function of tetrahydrobiopterin(BH_(4)).Results:Knockdown of METTL3 suppressed xenograft tumor growth and lung/lymph node metastasis in vivo.Mechanistically,we found that METTL3 combined with and stabilized PBX1 mRNAs.Chromatin immunoprecipitation(ChIP)and further experiments suggested that PBX1 acted as a transcription factor inducing GCH1 expression.Moreover,the METTL3-PBX1-GCH1 axis increased BH_(4)levels in GC cells,thereby promoting tumor progression.Conclusions:This study suggested that METTL3 enzymes promote tumor growth and lung/lymph node metastasis via METTL3-PBX1-GCH1 axis increasing BH_(4)levels in GC.