Energy-efficient joint UAV secure communication and 3D trajectory optimization assisted by reconfigurable intelligent surfaces in the presence of eavesdroppers

We consider a scenario where an unmanned aerial vehicle(UAV),a typical unmanned aerial system(UAS),transmits confidential data to a moving ground target in the presence of multiple eavesdroppers.Multiple friendly reconfigurable intelligent surfaces(RISs) help to secure the UAV-target communication and improve the energy efficiency of the UAV.We formulate an optimization problem to minimize the energy consumption of the UAV,subject to the mobility constraint of the UAV and that the achievable secrecy rate at the target is over a given threshold.We present an online planning method following the framework of model predictive control(MPC) to jointly optimize the motion of the UAV and the configurations of the RISs.The effectiveness of the proposed method is validated via computer simulations.

Design and nonlinearity compensation of Fabry-Perot type tunable optical filters for dynamic strain sensing systems

The collected spectrum of the fiber Bragg grating(FBG) and the loss of the detected optical power are discussed with respect to the 3-dB bandwidth of a Fabry-Perot(F-P) type tunable optical filter(TOF),respectively.And the optimized parameters of the TOF are obtained consequently.It is demonstrated that the relationship between the transmission wave-length of the TOF and its drive voltage is nonlinear.A new method to compensate the nonlinearity of the TOF is proposed.The linear sweeping of the transmission wavelength of the TOF is achieved through modifying the drive voltage using interpolation algorithm.It is observed that the average error and the maximum error of the transmission wavelength are reduced sharply under linear fit.The dynamic strain sensing is realized by use of a reference FBG and moving averaging algorithm in this system.

Review and Simulation of a Novel Formation Building Algorithm While Enabling Obstacle Avoidance

Technically, a group of more than two wheeled mobile robots working collectively towards a common goal are known as a multi-robot system. An increasing number of industries have implemented multi-robot systems to eliminate the risk of human injuries while working on hazardous tasks, and to improve productivity. Globally, engineers are continuously researching better, simple, and faster cooperative Control algorithms to provide a Control strategy where each agent in the robot formation can communicate effectively and achieve a consensus in their position, orientation and speed. This paper explores a novel Formation Building Algorithm and its global stability around a configuration vector. A simulation in MATLAB? was carried out to examine the performance of the Algorithm for two geometric formations and a fixed number of robots. In addition, an obstacle avoidance technique was presented assuming that all robots are equipped with range sensors. In particular, a uniform rounded obstacle is used to analyze the performance of the technique with the use of detailed geometric calculations.

Special Topic on Integrated Sensing and Communication(ISAC) Technologies for Future Wireless Communication

The radio communication division of the International Telecommunication Union(ITU-R)has recently adopted Integrated Sensing and Communication(ISAC)as a key usage scenario for IMT-2030/6G.The synergy of these two functionalities can facilitate a wide array of applications such as autonomous driving,smart cities,and industrial automation,where simultaneous data transmission and environmental sensing are crucial.The rationale of the ISAC is that a radio emission can simultaneously convey communication data from the transmitter to the receiver and extract environmental information from the scattered echoes.From a research perspective,ISAC opens new avenues for innovation in signal processing,hardware design,and network architecture,facilitating efficient utilization of system spectrum/power/hardware resources and pursuit of mutual benefits.It is anticipated that ISAC can improve spectral efficiency,reduce hardware costs,and enhance overall system capabilities.

Interference of selective higher-order modes in optical fibers

The interference of selective higher-order modes in optical fibers is investigated both theoretically and experimentally. It has been demonstrated that by coupling the LP01 mode in a step-index single-mode fiber (SMF) to the LP0m modes in step-index multimode fibers (MMFs) with different parameters, one can selectively generate higher-order modes and construct all-fiber interferometers. The research presented in this paper forms a basis of a new type of fiber devices with potential applications in fiber sensing, optical fiber communications, and optical signal processing.

Enhancement of signal-noise-ratio in a distributed polarization mode coupling detection system

A distributed polarization-mode coupling measurement system was designed and implemented using white light interferometry. It can be used for the measurement of polarization mode coupling in a high-birefringence fiber of up to i km. This system can be used in both fiber-optic sensors and optical fiber communications. Wavelet Transform was adopted in data processing to improve the signal-noise-ratio. The signal-noise-ratio of this system was improved more than 15 dB after denoising. The influence of denoising threshold on signal-noise-ratio and measurement accuracy was also discussed. Hilbert Transform and non-linear regression can be used in conjunction with Wavelet Transform to enhance the signal-noise-ratio and spatial resolution of this system.

Performance of LDPC Coded OTFS Systems over High Mobility Channels

The upcoming 6G wireless networks have to provide reliable communications in high-mobility scenarios at high carrier frequencies.However,high-mobility or high carrier frequencies will bring severe inter-carrier interference(ICI)to conventional orthogonal fre⁃quency-division multiplexing(OFDM)modulation.Orthogonal time frequency space(OTFS)modulation is a recently developing multi-carrier transmission scheme for wireless commu⁃nications in high-mobility environments.This paper evaluates the performance of coded OT⁃FS systems.In particular,we consider 5G low density parity check(LDPC)codes for OTFS systems based on 5G OFDM frame structures over high mobility channels.We show the per⁃formance of the OTFS systems with 5G LDPC codes when sum-product detection algorithm and iterative detection and decoding are employed.We also illustrate the effect of channel estimation error on the performance of the LDPC coded OTFS systems.

Autonomous UAV 3D trajectory optimization and transmission scheduling for sensor data collection on uneven terrains

This paper considers a time-constrained data collection problem from a network of ground sensors located on uneven terrain by an Unmanned Aerial Vehicle(UAV),a typical Unmanned Aerial System(UAS).The ground sensors harvest renewable energy and are equipped with batteries and data buffers.The ground sensor model takes into account sensor data buffer and battery limitations.An asymptotically globally optimal method of joint UAV 3D trajectory optimization and data transmission schedule is developed.The developed method maximizes the amount of data transmitted to the UAV without losses and too long delays and minimizes the propulsion energy of the UAV.The developed algorithm of optimal trajectory optimization and transmission scheduling is based on dynamic programming.Computer simulations demonstrate the effectiveness of the proposed algorithm.

GenAI4Sustainability:GPT and Its Potentials For Achieving UN’s Sustainable Development Goals

SINCE 2015,17 Sustainable Development Goals(SDGs)have been understood as more promising blueprints for a peaceful,prosperous,and sustainable future[1]which are formulated to seek a framework to address global challenging issues such as poverty,inequality,and pollution.

Finite-time economic model predictive control for optimal load dispatch and frequency regulation in interconnected power systems

This paper presents a finite-time economic model predictive control(MPC)algorithm that can be used for frequency regulation and optimal load dispatch in multi-area power systems.Economic MPC can be used in a power system to ensure frequency stability,real-time economic optimization,control of the system and optimal load dispatch from it.A generalized terminal penalty term was used,and the finite-time convergence of the system was guaranteed.The effectiveness of the proposed model predictive control algorithm was verified by simulating a power system,which had two areas connected by an AC tie line.The simulation results demonstrated the effectiveness of the algorithm.

Methodologies of Secret-Key Agreement Using Wireless Channel Characteristics

In this article, we give an overview of current research on shared secret-key agreement between two parties. This agreement is based on radio wireless channel characteristics. We discuss the advantages of this approach over traditional cryptographic mechanisms and present the theoretical background of this approach. We then give a detailed description of the key-agreement process and the threat model, and we summarize the typical performance metrics for shared secret-key agreement. There are four processes in shared secret-key agreement： sampling, quantization, information reconciliation, and privacy amplification. We classify prior and current research in this area according to innovation on these four processes. We conclude with a discussion of existing challenges and directions for future work.

Editorial:Special Topic on Future Advanced Satellite Communication Systems and Applications

In 2020,the world has faced unprecedented challenges in human history with the Covid-19 pandemic,but communication systems and technologies have helped tremendously for teleworking and teleconferences.The progress of new technologies,particularly for satellite communication systems and applications,is facilitating the global coverage.

Impact of demand growth on the capacity of long-duration energy storage under deep decarbonization

The weather-dependent uncertainty of wind and solar power generation presents a challenge to the balancing of power generation and demand in highly renewable electricity systems.Battery energy storage can provide flexibility to firm up the variability of renewables and to respond to the increased load demand under decarbonization scenarios.This paper explores how the battery energy storage capacity requirement for compressed-air energy storage(CAES)will grow as the load demand increases.Here we used an idealized lowest-cost optimization model to study the response of highly renewable electricity systems to the increasing load demand of California under deep decarbonization.Results show that providing bulk CAES to the zero-emission power system offers substantial benefits,but it cannot fully compensate for the 100%variability of highly renewable power systems.The capacity requirement of CAES increases by≤33.3%with a 1.5 times increase in the load demand and by≤50%with a two-times increase in the load demand.In this analysis,a zero-emission electricity system operating at current costs becomes more cost-effective when there is firm power generation.The least competitive nuclear option plays this role and reduces system costs by 16.4%,curtails the annual main node by 36.8%,and decreases the CAES capacity requirements by≤80.7%in the case of a double-load demand.While CAES has potential in addressing renewable variability,its widespread deployment is constrained by geographical,societal,and economic factors.Therefore,if California is aiming for an energy system that is reliant on wind and solar power,then an additional dispatchable power source other than CAES or similar load flexibility is necessary.To fully harness the benefits of bulk CAES,the development and implementation of cost-effective approaches are crucial in significantly reducing system costs.

Electrical Tracking,Erosion and Fire Retardancy Performance of Silicone Rubber Insulation Containing Aluminum Trihydrate,Graphene and Glass Fiber Additives

Silicone rubber composite is a priority electrical insulating material used in high-voltage outdoor insulation applications.Low electrical tracking/erosion and poor flame resistance performance of silicone rubber once ignited,substantially reduce its working life.This paper attempts to investigate tracking/erosion performance of room temperature vulcanized(RTV)silicone rubber along with flame retardant parameters using aluminum trihydrate(ATH),graphene nanosheets(GN)and milled glass fiber(GF)additives.The inclined plane test(IPT)was performed in line with criteria defined in IEC 60587 using step-up tracking voltage method while flame retardancy is evaluated according to ASTM E 1354.0 using a cone calorimeter.Results suggest 30% of ATH assists in improving physical tracking/erosion resistance of pristine silicone elastomer rubber by impeding development of leakage current and a great reduction in maximum average temperatures on the surface of RTV2.Further improvement in performance of RTV2 is achieved through introduction of 1%of GN and 5% of GF as seen in RTV4.Moreover,30% of ATH reduces heat release rate and smoke production rate,and this trend is improved with the introduction of GN/GF.RTV4 has pop up as the most promising silicone rubber composite with excellent electrical tracking,erosion,and flame resistance performance relative to its counterparts in this study.

Biochemical sensing in graphene-enhanced microfiber resonators with individual molecule sensitivity and selectivity

Photonic sensors that are able to detect and track biochemical molecules offer powerful tools for information acquisition in applications ranging from environmental analysis to medical diagnosis.The ultimate aim of biochemical sensing is to achieve both quantitative sensitivity and selectivity.As atomically thick films with remarkable optoelectronic tunability,graphene and its derived materials have shown unique potential as a chemically tunable platform for sensing,thus enabling significant performance enhancement,versatile functionalization and flexible device integration.Here,we demonstrate a partially reduced graphene oxide(prGO)inner-coated and fiber-calibrated Fabry-Perot dye resonator for biochemical detection.Versatile functionalization in the prGO film enables the intracavity fluorescent resonance energy transfer(FRET)to be chemically selective in the visible band.Moreover,by measuring the intermode interference via noise canceled beat notes and locked-in heterodyne detection with Hz-level precision,we achieved individual molecule sensitivity for dopamine,nicotine and single-strand DNA detection.This work combines atomic-layer nanoscience and high-resolution optoelectronics,providing a way toward high-performance biochemical sensors and systems.

Coordinated Demand Response of Rail Transit Load and Energy Storage System Considering Driving Comfort

Electric trains typically travel across the railway networks in an inter-provincial,inter-city and intra-city manner.The electric train generally serves as a load/source in tractive/brake mode,through which power networks and railway networks are closely coupled and mutually influenced.Based on the operational mode of rail trains and the characteristics of their load power,this paper proposes a coordinated optimal decisionmaking method of demand response for controllable load of rail trains and energy storage systems.First,a coordinated approach of dynamically adjusting the load of the controllable rail train in considering the driving comfort and energy storage battery is designed.Secondly,under the time conditions that satisfy the train’s operational diagram,the functional relationship between the train speed and the load power is presented.Based on this,in considering the constraints of the train’s arrival time,driving speed,motor power,and driving comfort,the capacity of energy storage batteries and other constraints,an optimization model for demand response in managing the traction power supply system under a two-part price and time-of-use(TOU)price is proposed.The objective is to minimize the energy consumption costs of rail transit trains,and optimize the speed trajectory of rail trains,the load power of traction system,and the output of energy storage batteries.

Location Verification Systems in Emerging Wireless Networks

As location-based techniques and applications have become ubiquitous in emerging wireless networks, the verification of location information has become more important. In recent years, there has been an explosion of activity related to lo- cation-verification techniques in wireless networks. In particular, there has been a specific focus on intelligent transport systems because of the mission-critical nature of vehicle location verification. In this paper, we review recent research on wireless location verification related to vehicular networks. We focus on location verification systems that rely on for- mal mathematical classification frameworks and show how many systems are either partially or fully encompassed by such frameworks.

APU-D* Lite: Attack Planning under Uncertainty Based on D* Lite

With serious cybersecurity situations and frequent network attacks,the demands for automated pentests continue to increase,and the key issue lies in attack planning.Considering the limited viewpoint of the attacker,attack planning under uncertainty is more suitable and practical for pentesting than is the traditional planning approach,but it also poses some challenges.To address the efficiency problem in uncertainty planning,we propose the APU-D*Lite algorithm in this paper.First,the pentest framework is mapped to the planning problem with the Planning Domain Definition Language(PDDL).Next,we develop the pentest information graph to organize network information and assess relevant exploitation actions,which helps to simplify the problem scale.Then,the APU-D*Lite algorithm is introduced based on the idea of incremental heuristic searching.This method plans for both hosts and actions,which meets the requirements of pentesting.With the pentest information graph as the input,the output is an alternating host and action sequence.In experiments,we use the attack success rate to represent the uncertainty level of the environment.The result shows that APU-D*Lite displays better reliability and efficiency than classical planning algorithms at different attack success rates.

Distributed Resource Allocation via Accelerated Saddle Point Dynamics

In this paper,accelerated saddle point dynamics is proposed for distributed resource allocation over a multi-agent network,which enables a hyper-exponential convergence rate.Specifically,an inertial fast-slow dynamical system with vanishing damping is introduced,based on which the distributed saddle point algorithm is designed.The dual variables are updated in two time scales,i.e.,the fast manifold and the slow manifold.In the fast manifold,the consensus of the Lagrangian multipliers and the tracking of the constraints are pursued by the consensus protocol.In the slow manifold,the updating of the Lagrangian multipliers is accelerated by inertial terms.Hyper-exponential stability is defined to characterize a faster convergence of our proposed algorithm in comparison with conventional primal-dual algorithms for distributed resource allocation.The simulation of the application in the energy dispatch problem verifies the result,which demonstrates the fast convergence of the proposed saddle point dynamics.

Tracking,erosion and thermal distribution of micro-AlN+nano-SiO_(2) co-filled silicone rubber for high-voltage outdoor insulation

Thermal depolymerisation induced tracking and erosion of polymeric insulators is one of the key insulation failure modes and this process adversely affects the reliability of power delivery networks.This study reports the tracking,erosion and thermal distribution of micron-AlN and micron-AlN+nano-SiO_(2)co-filled silicone rubber composites.A tracking-erosion model is presented to explain how the co-filled set of particles directly affects such mechanisms.Aluminium nitride(AlN:5-10μm)and silica(SiO_(2):20 nm)particles were procured for fabricating test samples.The inclined plane test according to IEC 60587 was carried out using tracking voltage method 2 with an initial applied voltage of 3 kV and a ramping rate of 0.25 kV/h over the duration of 240 min.Measurement results show co-filled composites exhibit significantly lower physical tracking and erosion as compared to micron-AlN filled composites.Thermal accumulation and average leakage current in co-filled composites are found noticeably lower than micron-filled counterparts.Moreover,the increased surface area of the combined co-filled particles in the composites provides better scattering and reduce secondary electron collision.This may impede the release of high energy causing thermal degradation.