Modeling and Performance Analysis of UAV-Aided Millimeter Wave Cellular Networks with Stochastic Geometry

UAV-aided cellular networks,millimeter wave(mm-wave)communications and multi-antenna techniques are viewed as promising components of the solution for beyond-5G(B5G)and even 6G communications.By leveraging the power of stochastic geometry,this paper aims at providing an effective framework for modeling and analyzing a UAV-aided heterogeneous cellular network,where the terrestrial base stations(TBSs)and the UAV base stations(UBSs)coexist,and the UBSs are provided with mm-wave and multi-antenna techniques.By modeling the TBSs as a PPP and the UBSs as a Matern hard-core point pro-´cess of type II(MPH-II),approximated but accurate analytical results for the average rate of the typical user of both tiers are derived through an approximation method based on the mean interference-to-signal ratio(MISR)gain.The influence of some relevant parameters is discussed in detail,and some insights into the network deployment and optimization are revealed.Numerical results show that some trade-offs are worthy of being considered,such as the antenna array size,the altitude of the UAVs and the power control factor of the UBSs.

Floquet spectrum and universal dynamics of a periodically driven two-atom system

We investigate the Floquet spectrum and excitation properties of a two-ultracold-atom system with periodically driven interaction in a three-dimensional harmonic trap.The interaction between the atoms is changed by varying the s-wave scattering length in two ways,the cosine and the square-wave modulations.It is found that as the driving frequency increases,the Floquet spectrum exhibits two main features for both modulations,the accumulating and the spreading of the quasienergy levels,which further lead to different dynamical behaviors.The accumulation is associated with collective excitations and the persistent growth of the energy,while the spread indicates that the energy is bounded at all times.The initial scattering length,the driving frequency and amplitude can all significantly change the Floquet spectrum as well as the dynamics.However,the corresponding relation between them is valid universally.Finally,we propose a mechanism for selectively exciting the system to one specific state by using the avoided crossing of two quasienergy levels,which could guide preparation of a desired state in experiments.

Online Learning-Based Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Networks

Mobile edge computing(MEC)-enabled satellite-terrestrial networks(STNs)can provide Internet of Things(IoT)devices with global computing services.Sometimes,the network state information is uncertain or unknown.To deal with this situation,we investigate online learning-based offloading decision and resource allocation in MEC-enabled STNs in this paper.The problem of minimizing the average sum task completion delay of all IoT devices over all time periods is formulated.We decompose this optimization problem into a task offloading decision problem and a computing resource allocation problem.A joint optimization scheme of offloading decision and resource allocation is then proposed,which consists of a task offloading decision algorithm based on the devices cooperation aided upper confidence bound(UCB)algorithm and a computing resource allocation algorithm based on the Lagrange multiplier method.Simulation results validate that the proposed scheme performs better than other baseline schemes.

Joint Optimization of Energy Consumption and Network Latency in Blockchain-Enabled Fog Computing Networks

Fog computing is considered as a solution to accommodate the emergence of booming requirements from a large variety of resource-limited Internet of Things(IoT)devices.To ensure the security of private data,in this paper,we introduce a blockchain-enabled three-layer device-fog-cloud heterogeneous network.A reputation model is proposed to update the credibility of the fog nodes(FN),which is used to select blockchain nodes(BN)from FNs to participate in the consensus process.According to the Rivest-Shamir-Adleman(RSA)encryption algorithm applied to the blockchain system,FNs could verify the identity of the node through its public key to avoid malicious attacks.Additionally,to reduce the computation complexity of the consensus algorithms and the network overhead,we propose a dynamic offloading and resource allocation(DORA)algorithm and a reputation-based democratic byzantine fault tolerant(R-DBFT)algorithm to optimize the offloading decisions and decrease the number of BNs in the consensus algorithm while ensuring the network security.Simulation results demonstrate that the proposed algorithm could efficiently reduce the network overhead,and obtain a considerable performance improvement compared to the related algorithms in the previous literature.

High-Level Security Dimension Evaluation of Blockchain BaaS System and Key Technology

In recent years,blockchain technology integration and application has gradually become an important driving force for new technological innovation and industrial transformation.While blockchain technology and applications are developing rapidly,the emerging security risks and obstacles have gradually become prominent.Attackers can still find security issues in blockchain systems and conduct attacks,causing increasing losses from network attacks every year.In response to the current demand for blockchain application security detection and assessment in all industries,and the insufficient coverage of existing detection technologies such as smart contract detectiontechnology,this paper proposes a blockchain core technology security assessment system model,and studies the relevant detection and assessment key technologies and systems.A security assessment scheme based on a smart contract and consensus mechanism detection scheme is designed.And the underlying blockchain architecture supports the traceability of detection results using super blockchains.Finally,the functionality and performance of the system were tested,and the test results show that the model and solutions proposed in this paper have good feasibility.

User Scheduling and Slicing Resource Allocation in Industrial Internet of Things

Heterogeneous base station deployment enables to provide high capacity and wide area coverage.Network slicing makes it possible to allocate wireless resource for heterogeneous services on demand.These two promising technologies contribute to the unprecedented service in 5G.We establish a multiservice heterogeneous network model,which aims to raise the transmission rate under the delay constraints for active control terminals,and optimize the energy efficiency for passive network terminals.A policygradient-based deep reinforcement learning algorithm is proposed to make decisions on user association and power control in the continuous action space.Simulation results indicate the good convergence of the algorithm,and higher reward is obtained compared with other baselines.

Assessment and Application of Beach Quality Based on Analytic Hierarchy Process in Yangkou Beach, Qingdao

The whole-beach quality assessment is the basis of building and preserving beautiful beaches.The beach quality assessment index system and assessment standard have been established based on the attributes of beaches(including the width,slope,landform,and types),sorting coefficient,and softness degree of surface sediment.The assessment weight of each index for quality evaluation was analyzed using the analytic hierarchy process,and comprehensive scores of selected beach profiles were calculated in accordance with the light assessment standard.A beach quality evaluation model based on index weight and scores was established in this paper.The factors of 12 profiles of Yangkou Beach in Qingdao City were surveyed to carry out a quality assessment,and the comprehensive scores of each profile were calculated in accordance with the evaluation model.The results showed that the quality of Yangkou Beach can be divided into four ratings:excellent,good,medium,and poor.The excellent-quality area includes a wide and flat dry beach zone and soft,flat,and clean intertidal and subtidal zones covered with well-sorted fine sand,and leisure sports,such as volleyball,running,and swimming,are suitable for tourists.The good-quality area features a slightly narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered with fine sand and a small tidal gully,and a small amount of foreign matter;leisure sports,such as walking and running,are suitable for tourists.This study recommends the building of fixed drainage ditches or underground culverts to reduce the tidal gully.The medium-quality area consisted of a narrow and dry beach zone,moderately soft and uneven intertidal and subtidal zones covered by poorly sorted medium sand,a tide ditch,and a small amount of foreign matter.In this area,walking is suitable for tourists.Sand should be supplemented in the intertidal zone.The poor-quality area contained a very narrow and dry beach zone covered with poor-sorted gravel,a very chaotic intertidal zone with a considerable amount of foreign matters,such as bricks and rocks,wide tidal ditches,and an uneven subtidal zone with some reefs;leisure sports are unsuitable here.Thus,foreign matter and reefs should be removed,and the dry beach zone should be supplemented with sand.Therefore,the beach quality assessment is a very useful tool for building beautiful beaches.

Tasks-Oriented Joint Resource Allocation Scheme for the Internet of Vehicles with Sensing, Communication and Computing Integration

With the development of artificial intelligence(AI)and 5G technology,the integration of sensing,communication and computing in the Internet of Vehicles(Io V)is becoming a trend.However,the large amount of data transmission and the computing requirements of intelligent tasks lead to the complex resource management problems.In view of the above challenges,this paper proposes a tasks-oriented joint resource allocation scheme(TOJRAS)in the scenario of Io V.First,this paper proposes a system model with sensing,communication,and computing integration for multiple intelligent tasks with different requirements in the Io V.Secondly,joint resource allocation problems for real-time tasks and delay-tolerant tasks in the Io V are constructed respectively,including communication,computing and caching resources.Thirdly,a distributed deep Q-network(DDQN)based algorithm is proposed to solve the optimization problems,and the convergence and complexity of the algorithm are discussed.Finally,the experimental results based on real data sets verify the performance advantages of the proposed resource allocation scheme,compared to the existing ones.The exploration efficiency of our proposed DDQN-based algorithm is improved by at least about 5%,and our proposed resource allocation scheme improves the m AP performance by about 0.15 under resource constraints.

Software defined intelligent satellite-terrestrial integrated networks:Insights and challenges

Satellite-Terrestrial integrated Networks(STNs)have been advocated by both academia and industry as a promising network paradigm to achieve service continuity and ubiquity.However,STNs suffer from problems including poor flexibility of network architecture,low adaptability to dynamic environments,the lack of network intelligence,and low resource utilization.To handle these challenges,a Software defined Intelligent STN(SISTN)architecture is introduced.Specifically,the hierarchical architecture of the proposal is described and a distributed deployment scheme for SISTNs controllers is proposed to realize agile and effective network management and control.Moreover,three use cases in SISTNs are discussed.Meanwhile,key techniques and their corresponding solutions are presented,followed by the identification of several open issues in SISTNs including compatibility with existing networks,the tradeoff between network flexibility and performance,and so on.

Towards the Deep Convergence of Communication and Computing in RAN: Scenarios, Architecture, Key Technologies, Challenges and Future Trends

To accommodate the diversified emerging use cases in 5G,radio access networks(RAN)is required to be more flexible,open,and versatile.It is evolving towards cloudification,intelligence and openness.By embedding computing capabilities within RAN,it helps to transform RAN into a natural cost effective radio edge computing platform,offering great opportunity to further enhance RAN agility for diversified services and improve users’quality of experience(Qo E).In this article,a logical architecture enabling deep convergence of communication and computing in RAN is proposed based on O-RAN.The scenarios and potential benefits of sharing RAN computing resources are first analyzed.Then,the requirements,design principles and logical architecture are introduced.Involved key technologies are also discussed,including heterogeneous computing infrastructure,unified computing and communication task modeling,joint communication and computing orchestration and RAN computing data routing.Followed by that,a VR use case is studied to illustrate the superiority of the joint communication and computing optimization.Finally,challenges and future trends are highlighted to provide some insights on the potential future work for researchers in this field.

AIGC Scenario Analysis and Research on Technology Roadmap of Internet Industry Application

The explosion of ChatGPT is considered to be a milestone in the normalization of artificial intelligence education applications.On the technical line,the cross-modal AI generation application based on human feedback system is accelerated.In the business model,the scenes to realize interactive functions are constantly enriched.This paper reviews the evolution process of AIGC,closely follows the current situation of the coexistence of business acceleration and technical worries in the application of artificial intelligence education,analyzes the application of AIGC education in 7 subdivided fields,and analyzes the optimization direction of application cases from the perspective of perception-cognition-creation technology maturity matrix.The 3 recommendations and 2 follow-up research directions will promote the scientific application of artificial intelligence education in the AIGC period.

Design and Research of Form Controlled Planar Folding Mechanism based on 4D Printing Technology

The use of non-smart materials in structural components and kinematic pairs allows for flexible assembly in practical applications and is promising for aerospace applications.However,this approach can result in a complex structure and excessive kinematic pairs,which limits its potential applications due to the difficulty in controlling and actuating the mechanism.While smart materials have been integrated into certain mechanisms,such integration is generally considered a unique design for specific cases and lacks universality.Therefore,organically combining universal mechanism design with smart materials and 4D printing technology,innovating mechanism types,and systematically exploring the interplay between structural design and morphing control remains an open research area.In this work,a novel form-controlled planar folding mechanism is proposed,which seamlessly integrates the control and actuation system with the structural components and kinematic pairs based on the combination of universal mechanism design with smart materials and 4D printing technology,while achieving self-controlled dimensional ratio adjustment under a predetermined thermal excitation.The design characteristics of the mechanism are analyzed,and the required structural design parameters for the preprogrammed design are derived using a kinematic model.Using smart materials and 4D printing technology,folding programs based on material properties and control programs based on manufacturing parameters are encoded into the form-controlled rod to achieve the preprogrammed design of the mechanism.Finally,two sets of prototype mechanisms are printed to validate the feasibility of the design,the effectiveness of the morphing control programs,and the accuracy of the theoretical analysis.This mechanism not only promotes innovation in mechanism design methods but also shows exceptional promise in satellite calibration devices and spacecraft walking systems.

Assessing high-energy x-ray and proton irradiation effects on electrical properties of P-GaN and N-GaN thin films

The effects of ionizing and displacement irradiation of high-energy x-ray and 2-MeV proton on GaN thin films were investigated and compared in this study.The electrical properties of both P-GaN and N-GaN,separated from power devices,were gauged for fundamental analysis.It was found that the electrical properties of P-GaN were improved as a consequence of the disruption of the Mg-H bond induced by high-dose x-ray irradiation,as indicated by the Hall and circular transmission line model.Specifically,under a 100-Mrad(Si)x-ray dose,the specific contact resistance pc of P-GaN decreased by 30%,and the hole carrier concentration increased significantly.Additionally,the atom displacement damage effect of a 2-MeV proton of 1×10^(13)p/cm^(2)led to a significant degradation of the electrical properties of P-GaN,while those of N-GaN remained unchanged.P-GaN was found to be more sensitive to irradiation than N-GaN thin film.The effectiveness of x-ray irradiation in enhancing the electrical properties of P-GaN thin films was demonstrated in this study.

Secure and Trusted Interoperability Scheme of Heterogeneous Blockchains Platform in IoT Networks

With the rapid development of the Internet of Things(IoT),there is an increasing need for interac-tion between different networks.In order to improve the level of interconnection,especially the interoper-ability of users/devices between different nodes is very important.In the IoT heterogeneous blockchain sce-nario,how to ensure the legitimacy of the chain and how to confirm the identity of cross-chain informa-tion users/devices become the key issues to be solved for blockchain interoperability.In this paper,we pro-pose a secure and trusted interoperability mechanism for IoT based on heterogeneous chains to improve the security of blockchain interoperability.In this mecha-nism,a primary sidechain architecture supporting au-thentication at both ends of the heterogeneous chain is designed.In addition,a distributed gateway archi-tecture is proposed for cross-chain authentication and protocol conversion.The security and performance analysis shows that our scheme is feasible and effec-tive in improving the security of cross-chain opera-tions in IoT.

Distributed Edge Cooperation and Data Collection for Digital Twins of Wide-Areas

Digital twins for wide-areas(DT-WA)can model and predict the physical world with high fidelity by incorporating an artificial intelligence(AI)model.However,the AI model requires an energy-consuming updating process to keep pace with the dynamic environment,where studies are still in infancy.To reduce the updating energy,this paper proposes a distributed edge cooperation and data collection scheme.The AI model is partitioned into multiple sub-models deployed on different edge servers(ESs)co-located with access points across wide-area,to update distributively using local sensor data.To reduce the updating energy,ESs can choose to become either updating helpers or recipients of their neighboring ESs,based on sensor quantities and basic updating convergencies.Helpers would share their updated sub-model parameters with neighboring recipients,so as to reduce the latter updating workload.To minimize system energy under updating convergency and latency constraints,we further propose an algorithm to let ESs distributively optimize their cooperation identities,collect sensor data,and allocate wireless and computing resources.It comprises several constraint-release approaches,where two child optimization problems are solved,and designs a largescale multi-agent deep reinforcement learning algorithm.Simulation shows that the proposed scheme can efficiently reduce updating energy compared with the baselines.

Design of a photonic crystal fiber polarization beam splitter with simple structure and ultra-wide bandwidth

A novel polarization beam splitter(PBS)based on dual-core photonic crystal fiber(DC-PCF)is proposed in this work.The proposed DC-PCF PBS contains two kinds of lattices and three kinds of air holes to form the asymmetrical elliptic dual-core structure.By using the full-vector finite element method,the propagation characteristics of the proposed DC-PCF PBS are investigated.The simulation results show that the bandwidth of the proposed DC-PCF PBS can reach to 340 nm,which covers the S+C+L+U communication bands,the shortest splitting length is 1.97 mm,and the maximum extinction ratio appears near wavelength 1550 nm.Moreover,the insertion loss of the proposed DC-PCF PBS is very low.It is believed that the proposed DC-PCF PBS has important applications in the field of all-optical communication and network.

Stability and multistability of synchronization in networks of coupled phase oscillators

Coupled phase oscillators usually achieve synchronization as the coupling strength among oscillators is increased beyond a critical value. The stability of synchronous state remains an open issue. In this paper, we study the stability of the synchronous state in coupled phase oscillators. It is found that numerical integration of differential equations of coupled phase oscillators with a finite time step may induce desynchronization at strong couplings. The mechanism behind this instability is that numerical accumulated errors in simulations may trigger the loss of stability of the synchronous state.Desynchronization critical couplings are found to increase and diverge as a power law with decreasing the integral time step. Theoretical analysis supports the local stability of the synchronized state. Globally the emergence of synchronous state depends on the initial conditions. Other metastable ordered states such as twisted states can coexist with the synchronous mode. These twisted states keep locally stable on a sparse network but lose their stability when the network becomes dense.

Dynamic MmWave Channel Reconstruction of MIMO OTA Testing for Handover Scenarios

The evaluation of handover performance is essential for ensuring seamless user experience under innovative application scenarios in the fifth generation(5G)and beyond era,including autonomous driving,mobile augmented and virtual reality.However,due to the hardware constrains of a sectored multiprobe anechoic chamber(SMPAC),switching among multiple channel models is of low precision with a high cost in traditional over-the-air(OTA)test solutions.In this paper,we present an efficient and repeatable emulation strategy to reconstruct dynamic millimeter-wave(mm Wave)channels in laboratories for multiple-input multiple-output(MIMO)mobile devices.Firstly,we propose a novel evaluation metric,called average power angular spectrum similarity percentage(APSP),which minimizes the unexpected impact induced by the indefinite condition of adaptive antenna arrays in mm Wave terminals during handover process.Moreover,we propose a partitioned probe configuration strategy by designing a beam directivitybased switching circuit,which enables quick changes of probe configurations in SMPAC.Simulation results demonstrate the effectiveness of the proposed algorithms,thus providing a guideline for the reconstruction of the dynamic channel in different scenarios with resource limitation.

System Outage Probability and Diversity Analysis of a SWIPT Based Two-Way DF Relay Network Under Transceiver Hardware Impairments

This paper investigates the system outage performance of a simultaneous wireless information and power transfer(SWIPT)based two-way decodeand-forward(DF)relay network,where potential hardware impairments(HIs)in all transceivers are considered.After harvesting energy and decoding messages simultaneously via a power splitting scheme,the energy-limited relay node forwards the decoded information to both terminals.Each terminal combines the signals from the direct and relaying links via selection combining.We derive the system outage probability under independent but non-identically distributed Nakagami-m fading channels.It reveals an overall system ceiling(OSC)effect,i.e.,the system falls in outage if the target rate exceeds an OSC threshold that is determined by the levels of HIs.Furthermore,we derive the diversity gain of the considered network.The result reveals that when the transmission rate is below the OSC threshold,the achieved diversity gain equals the sum of the shape parameter of the direct link and the smaller shape parameter of the terminalto-relay links;otherwise,the diversity gain is zero.This is different from the amplify-and-forward(AF)strategy,under which the relaying links have no contribution to the diversity gain.Simulation results validate the analytical results and reveal that compared with the AF strategy,the SWIPT based two-way relaying links under the DF strategy are more robust to HIs and achieve a lower system outage probability.

Stochastic programming based multi-arm bandit offloading strategy for internet of things

In order to solve the high latency of traditional cloud computing and the processing capacity limitation of Internet of Things(IoT)users,Multi-access Edge Computing(MEC)migrates computing and storage capabilities from the remote data center to the edge of network,providing users with computation services quickly and directly.In this paper,we investigate the impact of the randomness caused by the movement of the IoT user on decision-making for offloading,where the connection between the IoT user and the MEC servers is uncertain.This uncertainty would be the main obstacle to assign the task accurately.Consequently,if the assigned task cannot match well with the real connection time,a migration(connection time is not enough to process)would be caused.In order to address the impact of this uncertainty,we formulate the offloading decision as an optimization problem considering the transmission,computation and migration.With the help of Stochastic Programming(SP),we use the posteriori recourse to compensate for inaccurate predictions.Meanwhile,in heterogeneous networks,considering multiple candidate MEC servers could be selected simultaneously due to overlapping,we also introduce the Multi-Arm Bandit(MAB)theory for MEC selection.The extensive simulations validate the improvement and effectiveness of the proposed SP-based Multi-arm bandit Method(SMM)for offloading in terms of reward,cost,energy consumption and delay.The results showthat SMMcan achieve about 20%improvement compared with the traditional offloading method that does not consider the randomness,and it also outperforms the existing SP/MAB based method for offloading.