NOMA-Based UAV-Aided Networks for Emergency Communications

High spectrum efficiency(SE)requirement and massive connections are the main challenges for the fifth generation(5G)and beyond 5G(B5G)wireless networks,especially for the case when Internet of Things(IoT)devices are located in a disaster area.Non-orthogonal multiple access(NOMA)-based unmanned aerial vehicle(UAV)-aided network is emerging as a promising technique to overcome the above challenges.In this paper,an emergency communications framework of NOMA-based UAV-aided networks is established,where the disasters scenarios can be divided into three broad categories that have named emergency areas,wide areas and dense areas.First,a UAV-enabled uplink NOMA system is established to gather information from IoT devices in emergency areas.Then,a joint UAV deployment and resource allocation scheme for a multi-UAV enabled NOMA system is developed to extend the UAV coverage for IoT devices in wide areas.Furthermore,a UAV equipped with an antenna array has been considered to provide wireless service for multiple devices that are densely distributed in disaster areas.Simulation results are provided to validate the effectiveness of the above three schemes.Finally,potential research directions and challenges are also highlighted and discussed.

Communication Mechanism and Algorithm of Composite Location Analysis of Emergency Communication based on Rail

The emergency communication system based on rail is an unconventional emergency communication mode,it is a complement equipment for that conventional communication system can’t work while tunnel mine accident occurs.Medium of transmission channel is the widely existing rail in the tunnel.In this paper we analyzed the characteristics of the rail transmission channel,verified the feasibility that information is transmitted by vibration signal in rail,we proposed the realization plan of the system.Communication protocol and processing mechanism suitable for rail transmission are designed according to the characteristics of channel bandwidth and low data transmission.Information communication with low bit rate and low bit error is realized in the communication simulation model.In the simplified model,we realized to transmit recognition speech information,and the error rate of the key text information is low to accept.The most concerned problem of personnel location in the mine disaster rescue is proposed,the composite algorithm is based on the model of signal amplitude attenuation,key node information and data frame transmission delay.Location information of hitting point can be achieved within the simplified model of the experiment.Furthermore,we discuss the characteristics of vibration signals passing through different channels.

Multi-Objective Bacterial Foraging Optimization Algorithm Based on Effective Area in Cognitive Emergency Communication Networks

Cognitive emergency communication net-works can meet the requirements of large capac-ity,high density and low delay in emergency com-munications.This paper analyzes the properties of emergency users in cognitive emergency communi-cation networks,designs a multi-objective optimiza-tion and proposes a novel multi-objective bacterial foraging optimization algorithm based on effective area(MOBFO-EA)to maximize the transmission rate while maximizing the lifecycle of the network.In the algorithm,the effective area is proposed to prevent the algorithm from falling into a local optimum,and the diversity and uniformity of the Pareto-optimal solu-tions distributed in the effective area are used to eval-uate the optimization algorithm.Then,the dynamic preservation is used to enhance the competitiveness of excellent individuals and the uniformity and diversity of the Pareto-optimal solutions in the effective area.Finally,the adaptive step size,adaptive moving direc-tion and inertial weight are used to shorten the search time of bacteria and accelerate the optimization con-vergence.The simulation results show that the pro-posed MOBFO-EA algorithm improves the efficiency of the Pareto-optimal solutions by approximately 55%compared with the MOPSO algorithm and by approx-imately 60%compared with the MOBFO algorithm and has the fastest and smoothest convergence.

Mega-Constellations Based TT&C Resource Sharing: Keep Reliable Aeronautical Communication in an Emergency

With the development of the transportation industry, the effective guidance of aircraft in an emergency to prevent catastrophic accidents remains one of the top safety concerns. Undoubtedly, operational status data of the aircraft play an important role in the judgment and command of the Operational Control Center(OCC). However, how to transmit various operational status data from abnormal aircraft back to the OCC in an emergency is still an open problem. In this paper, we propose a novel Telemetry, Tracking,and Command(TT&C) architecture named Collaborative TT&C(CoTT&C) based on mega-constellation to solve such a problem. CoTT&C allows each satellite to help the abnormal aircraft by sharing TT&C resources when needed, realizing real-time and reliable aeronautical communication in an emergency. Specifically, we design a dynamic resource sharing mechanism for CoTT&C and model the mechanism as a single-leader-multi-follower Stackelberg game. Further, we give an unique Nash Equilibrium(NE) of the game as a closed form. Simulation results demonstrate that the proposed resource sharing mechanism is effective, incentive compatible, fair, and reciprocal. We hope that our findings can shed some light for future research on aeronautical communications in an emergency.

Evolutionary PSO-based emergency monitoring geospatial edge service chain in the emergency communication network

Emergency communication networks play a vital role in disaster monitoring,transmission,and application during disaster emergency response(DER),however,the performance and stability of edge nodes in the emergency communication networks are often weak due to limited communication and computation resources.This weakness directly affects the quality,of service(Qos)of the geospatial edge service(GES)chains involved in emergency monitoring.Existing research predominantly addresses service compositions in stable environments,neglecting the aggregation of efficient and robust GES chains in emergency communication networks.This study proposes an evolutionary_particie swarm optimization(EPSO)-based emergency monitoring GES chain in an_emergency communication network.it includes a GES chain model of emergency environment monitoring for tailing areas,as well as the designs of the particle chromosome encoding method,fitness evaluation model,and particle chromosome swarm update operators of the EPSO-based GES chain.Finally,the study conducts emergency environment monitoring experiments for tailing areas using the proposed method.Experiments results demonstrate that the proposed method significantly enhances the efficiency,stability,and reliability of emergency monitoring GEs chains in the emergency communication network.This is crucial to providing fast and reliable services for DER during natural disasters.

An Unmanned Aerial Vehicle Flight Formation for Enhanced Emergency Communication Based on Conformal Antenna Design

Benefiting from the inherent superiorities in flexibility and mobility,the use of unmanned aerial vehicles(UAVs)as flying base stations for wireless coverage has been of significant interest,especially for rescue services.This work concerns the reliable emergency communication based on commercial micro-sized UAVs due to their high availability and low cost.To decrease the weight overloads and to improve the power efficiency,a UAV body conformal and omnidirectional antenna is first presented based on the characteristic mode analysis.To extend the wireless coverage and to improve the communication quality of the UAV network,a UAV flight formation is then proposed and analyzed.In addition,the propagation analyses for the proposed UAV transmitter designs are performed in a realistic hilly canyon region.Simulations and comparisons are presented to demonstrate the effectiveness of the proposed designs in emergency communications and performance enhancement through the UAV flight formation.

UAV-Aided Networks for Emergency Communications in Areas with Unevenly Distributed Users

Nowadays,daily human life is closely intertwined with various networks.When natural disasters or malicious attacks break out,the failure of communication infrastructure due to direct destruction or indirect impact tends to cause a massive outage of communications.Emergency communication networks play a significant role in rescue operations.Recently,a flexible and efficient solution has been provided for emergency communications using unmanned aerial vehicles(UAVs).By means of their excellent characteristics,UAVs,serving as aerial base stations(ABSs),can be rapidly deployed to temporarily rebuild a damaged communication network to restore the users’connectivity.In this study,we investigate the use of UAVs as ABSs for an emergency communication scene where user equipment is unevenly distributed and the communication infrastructure has completely failed due to a severe disaster.Effective communication probability(ECP),which integrates throughput coverage and connectivity,is used to evaluate the performance of a communication network.Through simulations,we analyze communication improvements that can be obtained by the flexible deployment of ABSs.The results show a noticeable increase in ECP when some ABSs are deployed in optimal locations.

Lightweight Trusted Security for Emergency Communication Networks of Small Groups

Public communication infrastructures are susceptible to disasters. Thus, the Emergency Communication Networks(ECNs) of small groups are necessary to maintain real-time communication during disasters. Given that ECNs are self-built by users, the unavailability of infrastructures and the openness of wireless channels render them insecure. ECN security, however, is a rarely studied issue despite of its importance. Here, we propose a security scheme for the ECNs of small groups. Our scheme is based on the optimized Byzantine Generals’ Problem combined with the analysis of trusted security problems in ECNs. Applying the Byzantine Generals’ Problem to ECNs is a novel approach to realize two new functions, debugging and error correction, for ensuring system consistency and accuracy. Given the limitation of terminal devices, the lightweight fast ECDSA algorithm is introduced to guarantee the integrity and security of communication and the efficiency of the network. We implement a simulation to verify the feasibility of the algorithm after theoretical optimization.

The Development of Emergency Communication Device for Tianwen-1 Probe

Mars is one of the most valuable planets for space exploration.After entering the entry descent and landing(EDL)phase,the spacecraft would carry out a series of procedural deceleration operations and achieve soft landing on the surface of Mars.In the process of EDL,the landing platform would encounter a series of irreversible incidents within environmental unpredictability,making this process highly risky.The emergency communication device plays an important role if in the Mars Exploration Program.It can capture and store key dynamic parameters during EDL phase,enabling a high probability of survival in the occurrence of a faulty condition.It can also send the stored data to the Mars obit probe when the communication condition is met.This paper presents a scheme design for the emergency communication device based on its functionality and performance requirements.It includes the design proposal,simulation results,reliability analysis,technical risks and control measures,inheritance and performance compliance which verifies the rationality and correctness of the design.

A Survey on the Role of Complex Networks in IoT and Brain Communication

Complex networks on the Internet of Things(IoT)and brain communication are the main focus of this paper.The benefits of complex networks may be applicable in the future research directions of 6G,photonic,IoT,brain,etc.,communication technologies.Heavy data traffic,huge capacity,minimal level of dynamic latency,etc.are some of the future requirements in 5G+and 6G communication systems.In emerging communication,technologies such as 5G+/6G-based photonic sensor communication and complex networks play an important role in improving future requirements of IoT and brain communication.In this paper,the state of the complex system considered as a complex network(the connection between the brain cells,neurons,etc.)needs measurement for analyzing the functions of the neurons during brain communication.Here,we measure the state of the complex system through observability.Using 5G+/6G-based photonic sensor nodes,finding observability influenced by the concept of contraction provides the stability of neurons.When IoT or any sensors fail to measure the state of the connectivity in the 5G+or 6G communication due to external noise and attacks,some information about the sensor nodes during the communication will be lost.Similarly,neurons considered sing the complex networks concept neuron sensors in the brain lose communication and connections.Therefore,affected sensor nodes in a contraction are equivalent to compensate for maintaining stability conditions.In this compensation,loss of observability depends on the contraction size which is a key factor for employing a complex network.To analyze the observability recovery,we can use a contraction detection algorithm with complex network properties.Our survey paper shows that contraction size will allow us to improve the performance of brain communication,stability of neurons,etc.,through the clustering coefficient considered in the contraction detection algorithm.In addition,we discuss the scalability of IoT communication using 5G+/6G-based photonic technology.

InN-Based Ill-Nitrides; A New Emerging Material System for Application in Optical Communications

The fact that InN has a direct bandgap of 0.75eV enables InN-based nitrides devices to cover the wavelength range from UV region to 1.8μm, therefore, emerging as a new material system for optical communication applications.

RIS-SWIPT for Batteryless Users in Disaster Areas

For trapped users in disaster areas,the available energy of affected user equipment(UE)is limited due to the breakdown of the ground power system.When complex geographical condition prevents ground emergency vehicles from reaching disaster-stricken areas,unmanned aerial vehicle(UAV)can effectively work as a temporary aerial base station for serving terrestrial trapped users.Simultaneous wireless information and power transfer(SWIPT)system is intriguing for distributed batteryless users(BUs)by transferring data and energy simultaneously.However,how to achieve the maximum energy efficiency(EE)and energy transfer efficiency(ETE)for distributed BUs in UAV-enabled SWIPT systems is not very clear.In this paper,we develop three novel reconfigurable intelligent surface(RIS)-based SWIPT algorithms to solve this nonconvex joint optimization problem using deep reinforcement learning(RL)algorithms.Through the deployment of RIS-assisted UAVs,we aim to maximize the EE along with the ETE via jointly designing the UAV trajectory,the phase matrix,and the power splitting ratio within strict time and energy constraints.The obtained numerical results show that our developed RL-based algorithms can effectively improve the cost time,the average charging rate,data rate,and the EE/ETE performance of the RIS-assisted SWIPT systems as compared with benchmark solutions.