Sum-Rate Optimization for Visible-Light-Band UAV Networks based on Particle Swarm Optimization

The mobility nature of unmanned aerial vehicles (UAVs) takes them into high consideration in military, public, and civilian applications in recent years. However, scaling out millions of UAVs in the air will inevitably lead to a more crowded radio frequency (RF) spectrum. Therefore, researchers have been focused on new technologies such as millimeter-wave, Terahertz, and visible light communications (VLCs) to alleviate the spectrum crunch problem. VLC has shown its great potential for UAV networking because of its high data rate, interference-free to legacy RF spectrum, and low-complex frontends. While the physical layer design of the VLC system has been extensively investigated, visible-light-band networking is still in its infancy because of the intermittent link availability caused by blockage and miss-alignment among transceivers. Fortunately, drones can be deployed dynamically at network runtime to establish line-of-sight (LOS) links to users in blockage-rich environments. In this article, we first formulate a sum-rate optimization problem for visible-light-band UAV networks by jointly control the real-time position and orientations of drones. We then propose a solution algorithm based on particle swarm optimization (PSO). The simulation results show that the proposed algorithm can converge in 10 to 20 iteration time and can result in up to 24% performance gain compared to that in heuristic-central-point drone deployment

Q-Learning for Sum-Throughput Optimization in Wireless Visible-Light UAV Networks

Unmanned Aerial Vehicles (UAVs) Have Been Adopted as Aerial Base Stations (ABSs) to Provide Wireless Connectivity to Ground Users in Events of Increased Network Demand, and Points-Of-Failure Infrastructure (Such as in Disasters). However, with the Existing Crowded Radio Frequency (RF) Spectrum, UAV ABSs Cannot Provide High-Data-Rate Communication Required in 5G and beyond. to Address This Challenge, Visible Light Communication (VLC) is Proposed to Be Equipped on UAVs to Take Advantage of the Flexible and On-Demand Deployment Feature of the UAV, and the High-Data-Rate Communication of the VLC. However, VLC Has Strong Alignment Requirements between Transceivers, Therefore, How to Determine the Position and Orientation of the UAV is Critically Important for Sum-Throughput Improvement. in This Paper, We Propose Two Q-Learning based Methods to Maximize the Sum throughput of the Wireless Visible-Light UAV Network by Jointly Controlling the Position and Orientation of the UAV. the Results Show that the Proposed Approaches Can Achieve a Network-Wide Data Rate Very Close to the Optimal Solution Obtained by Exhaustive Search and Outperform Up to 18% Compared with the Intuitive Centroid-Based Method. Computation Complexity is Also Evaluated, Where Results Showing that the Proposed Two Q-Learning based Methods Can Both Consume Less Computational Time, I.e., Approximately 9 Times and 210 Times Less on Average Than that of the Exhaustive Search Approach

Programmable Software-Defined Testbed for Visible Light UAV Networks: Architecture Design and Implementation

As of Today, There Has Been Increasing Research on Designing Optimization Algorithms and Intelligent Network Control Methods for Visible Light Unmanned Aerial Vehicles (UAV) Networks to Provide Pervasive and Broadband Connections. for Those Theoretical Analysis based Algorithms, there is an Urgent Need to Have a Visible Light UAV Network Platform that Can Help Evaluate the Proposed Algorithms in Real-World Scenarios. However, to the Best of Our Knowledge, there is Currently No Dedicated High Data Rate and Flexible Visible Light UAV Networking Prototype. to Bridge This Gap, in This Paper, We First Design a Novel Programmable Software-Defined Architecture for Visible Light UAV Networking, Including Control Plane, Network Plane, Signal Processing Chain and Front-Ends Plane, and Ground Facility Plane. We Then Implement a Prototype and Conduct Numerous Experiments to Validate the Feasibility of Visible-Light UAV Networks and Further Evaluate the System Performance Pertaining to Achievable Data Rate and Transmission Distance. the Real-Time Video Streaming Experimental Results Show that Up to 550 Kbps Data Rate and a Maximum Distance of 7 Meters Can Be Achieved

Compressed Sensing based Low-Power Multi-View Video Coding and Transmission in Wireless Multi-Path Multi-Hop Networks

Wireless Multimedia Sensor Network (WMSN) is increasingly being deployed for surveillance, monitoring and Internet-of-Things (IoT) sensing applications where a set of cameras capture and compress local images and then transmit the data to a remote controller. Such captured local images may also be compressed in a multi-view fashion to reduce the redundancy among overlapping views. In this paper, we present a novel paradigm for compressed-sensing-enabled multi-view coding and streaming in WMSN. We first propose a new encoding and decoding architecture for multi-view video systems based on Compressed Sensing (CS) principles, composed of cooperative sparsity-aware block-level rate-adaptive encoders, feedback channels and independent decoders. The proposed architecture leverages the properties of CS to overcome many limitations of traditional encoding techniques, specifically massive storage requirements and high computational complexity. Then, we present a modeling framework that exploits the aforementioned coding architecture. The proposed mathematical problem minimizes the power consumption by jointly determining the encoding rate and multi-path rate allocation subject to distortion and energy constraints. Extensive performance evaluation results show that the proposed framework is able to transmit multi-view streams with guaranteed video quality at lower power consumption

Extensive Thiol Profiling for Assessment of Intracellular Redox Status in Cultured Cells by HPLC-MS/MS

Oxidative stress may contribute to the pathology of many diseases, and endogenous thiols, especially glutathione (GSH) and its metabolites, play essential roles in the maintenance of normal redox status. Understanding how these metabolites change in response to oxidative insult can provide key insights into potential methods of prevention and treatment. Most existing methodologies focus only on the GSH/GSH disulfide (GSSG) redox couple, but GSH regulation is highly complex and depends on several pathways with multiple redox-active sulfur-containing species. In order to more fully characterize thiol redox status in response to oxidative insult, a high-performance liquid chromatography with tandem mass spectrometry (HPLC-MS/MS) method was developed to simultaneously determine seven sulfur-containing metabolites, generating a panel that systematically examines several pathways involved in thiol metabolism and oxidative stress responses. The sensitivity (LOQ as low as 0.01 ng/mL), accuracy (88-126% spike recovery), and precision (≤ 12% RSD) were comparable or superior to those of existing methods. Additionally, the method was used to compare the baseline thiol profiles and oxidative stress responses of cell lines derived from different tissues. The results revealed a previously unreported response to oxidative stress in lens epithelial (B3) cells, which may be exploited as a new therapeutic target for oxidative-stress-related ocular diseases. Further application of this method may uncover new pathways involved in oxidative-stress-related diseases and endogenous defense mechanisms

Local transformation of mixed states of two qubits to Bell diagonal states

The optimal entanglement manipulation for a single copy of mixed states of two qubits is to transform it to a Bell diagonal state. In this paper we derive an explicit form of the local operation that can realize such a transformation. The result obtained is universal for arbitrary entangled two-qubit states and it discloses that the corresponding local filter is not unique for density matrices with rank $n=2$ and can be exclusively determined for that with $n=3$ and 4. As illustrations, a four-parameters family of mixed states are explored, the local filter as well as the transformation probability are given explicitly, which verify the validity of the general result.Comment: 5 pages, to be published in Phys. Rev.

Rhodium(II)-catalyzed stereocontrolled synthesis of dihydrofuran-3-imines from 1-Tosyl-1,2,3-triazoles

Rhodium(II) acetate catalyzes the denitrogenative transformation of 5-substituted and 4,5-disubstituted 1-sulfonyl-1,2,3-triazoles with pendent allyl and propargyl ether motifs to oxonium ylides that undergo [2,3]-sigmatropic rearrangement to give substituted dihydrofuran-3-imines in high yield and diastereoselectivity

Discovery of a chemical probe for the L3MBTL3 methyllysine reader domain

We describe the discovery of UNC1215, a potent and selective chemical probe for the methyl-lysine (Kme) reading function of L3MBTL3, a member of the malignant brain tumor (MBT) family of chromatin interacting transcriptional repressors. UNC1215 binds L3MBTL3 with a Kd of 120 nM, competitively displacing mono- or dimethyl-lysine containing peptides, and is greater than 50-fold selective versus other members of the MBT family while also demonstrating selectivity against more than 200 other reader domains examined. X-ray crystallography identified a novel 2:2 polyvalent mode of interaction. In cells, UNC1215 is non-toxic and binds directly to L3MBTL3 via the Kme-binding pocket of the MBT domains. UNC1215 increases the cellular mobility of GFP-L3MBTL3 fusion proteins and point mutants that disrupt the Kme binding function of GFP-L3MBTL3 phenocopy the effects of UNC1215. Finally, UNC1215 demonstrates a novel Kme-dependent interaction of L3MBTL3 with BCLAF1, a protein implicated in DNA damage repair and apoptosis

FLight: Toward Programmable Visible-Light-Band Wireless UAV Networking

Wireless unmanned aerial vehicle (UAV) networking has been unleashed to be a key technology to enable massive numbers of novel applications in future Internet of Things (IoTs) and 5G networks. However, scaling out of zillions of mobile devices, drones and objects in IoT will inevitably lead to the dreaded spectrum crunch problem. To alleviate the scarce radio spectrum problem, in this paper, we envision using visible light communication (VLC) for wireless UAV networks to unlock the capacity and propose FLight, a programmable visible-light-band wireless UAV networking system. Unlike RF communications, two main challenges in FLight are (i) limited network coverage because of significant pass loss, and (ii) intermittent visible light connections due to blockage-rich environments. In this paper, we discuss the key research components and open challenges in implementing FLight. By combining VLC and drone networking, FLight opens the way for a new class of applications that will benefit from ground-air and air-air communication