ETM-IoT:Energy-Aware Threshold Model for Heterogeneous Communication in the Internet of Things

The internet of things(IoT)has a wide variety of applications,which in turn raisesmany challenging issues.IoT technology enables devices to closely monitor their environment,providing context-aware intelligence based on the real-time data collected by their sensor nodes.The IoT not only controls these devices but also monitors their user’s behaviour.One of the major issues related to IoT is the need for an energy-efficient communication protocol which uses the heterogeneity and diversity of the objects connected through the internet.Minimizing energy consumption is a requirement for energyconstrained nodes and outsourced nodes.The IoT nodes deployed in different geographical regions typically have different energy levels.This paper focuses on creating an energy-efficient protocol for IoTwhich can deal with the clustering of nodes and the cluster head selection process.An energy thresholdmodel is developed to select the appropriate cluster heads and also to ensure uniform distribution of energy to those heads andmember nodes.The proposed model envisages an IoT network with three different types of nodes,described here as advanced,intermediate and normal nodes.Normal nodes are first-level nodes,which have the lowest energy use;intermediate nodes are second-level nodes,which have a medium energy requirement;and the advanced class are thirdlevel nodes with the highest energy use.The simulation results demonstrate that the proposed algorithm outperforms other existing algorithms.In tests,it shows a 26%improvement in network lifetime compared with existing algorithms.

A Secure Key Management Scheme for Heterogeneous Secure Vehicular Communication Systems

Intelligent transportation system （ITS） is proposed as the most effective way to improve road safety and traffic efficiency. However, the future of ITS for large scale transportation infrastructures deployment highly depends on the security level of vehicular communication systems （VCS）. Security applications in VCS are fulfilled through secured group broadcast. Therefore, secure key management schemes are considered as a critical research topic for network security. In this paper, we propose a framework for providing secure key management within heterogeneous network. The seeurity managers （SMs） play a key role in the framework by retrieving the vehicle departnre infi^rmation, encapsulating block to transport keys and then executing rekeying to vehicles within the same security domain. The first part of this framework is a novel Group Key Management （GKM） scheme basing on leaving probability （LP） of vehicles to depart current VCS region. Vehicle＇s LP factor is introduced into GKM scheme to achieve a more effieient rekeying scheme and less rekeying costs. The second component of the framework using the blockchain concept to simplify the distributed key management in heterogeneous VCS domains. Extensive simulations and analysis are provided to show the effectiveness and effieiency of the proposed framework： Our GKM results demonstrate that probability-based BR reduees rekeying eost compared to the benchmark scheme, while the blockchain deereases the time eost of key transmission over heterogeneous net-works.

Deep reinforcement learning-based resource allocation for D2D communications in heterogeneous cellular networks

Device-to-Device(D2D)communication-enabled Heterogeneous Cellular Networks(HCNs)have been a promising technology for satisfying the growing demands of smart mobile devices in fifth-generation mobile networks.The introduction of Millimeter Wave(mm-wave)communications into D2D-enabled HCNs allows higher system capacity and user data rates to be achieved.However,interference among cellular and D2D links remains severe due to spectrum sharing.In this paper,to guarantee user Quality of Service(QoS)requirements and effectively manage the interference among users,we focus on investigating the joint optimization problem of mode selection and channel allocation in D2D-enabled HCNs with mm-wave and cellular bands.The optimization problem is formulated as the maximization of the system sum-rate under QoS constraints of both cellular and D2D users in HCNs.To solve it,a distributed multiagent deep Q-network algorithm is proposed,where the reward function is redefined according to the optimization objective.In addition,to reduce signaling overhead,a partial information sharing strategy that does not observe global information is proposed for D2D agents to select the optimal mode and channel through learning.Simulation results illustrate that the proposed joint optimization algorithm possesses good convergence and achieves better system performance compared with other existing schemes.

Study on QoS and Communications Capacity in Heterogeneous Network Convergence

To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to be considered and solved in heterogeneous network convergence.Key technologies for a secured QoS and communications capacity analysis under heterogeneous environment are important subjects for research.Key technologies for a secured QoS are mainly on radio resource management algorithms covering Call Admission Control(CAC) algorithm,vertical handover algorithm,heterogeneous resource allocation algorithm and network selection algorithm.The applications of a novel multi-hop in heterogeneous convergence system serve the purposes of network coverage expansion,transmission power reduction,system communication capacity and throughput increase.

ZTE Communications Special Issue on Channel Measurement and Modeling for Heterogeneous 5G

While cellular networks have continuously evolved in re- cent years, the industry has clearly seen unprecedented chal- lenges to meet the exponentially growing expectations in the near future. The 5G system is facing grand challenges such as the ever-increasing traffic volumes and remarkably diver- sified services connecting humans and machines alike. As a result, the future network has to deliver massively increased capacity, greater flexibility, incorporated computing capabili- ty, support of significantly extended battery lifetime, and ac- commodation of varying payloads with fast setup and low latency, etc. In particular, as 5G requires more spectrum resource, higher frequency bands are desirable. Nowadays, millimeter wave has been widely accepted as one of the main communication bands for 5G.

ZTE Communications Special Issue on Channel Measurement and Modeling for Heterogeneous 5G

While cellular networks have continuously evolved in recent years, the industry has clearly seen unprecedented challenges to meet the exponentially growing expectations in the near future.

Cyclic-Pursuit-Based Circular Formation Control of Mobile Agents with Limited Communication Ranges and Communication Delays

This article addresses the circular formation control problem of a multi-agent system moving on a circle in the presence of limited communication ranges and communication delays.To minimize the number of communication links,a novel distributed controller based on a cyclic pursuit strategy is developed in which each agent needs only its leading neighbour’s information.In contrast to existing works,we propose a set of new potential functions to deal with heterogeneous communication ranges and communication delays simultaneously.A new framework based on the admissible upper bound of the formation error is established so that both connectivity maintenance and order preservation can be achieved at the same time.It is shown that the multi-agent system can be driven to the desired circular formation as time goes to infinity under the proposed controller.Finally,the effectiveness of the proposed method is illustrated by some simulation examples.

Federated Learning for 6G:A Survey From Perspective of Integrated Sensing,Communication and Computation

With the rapid advancements in edge computing and artificial intelligence,federated learning(FL)has gained momentum as a promising approach to collaborative data utilization across organizations and devices,while ensuring data privacy and information security.In order to further harness the energy efficiency of wireless networks,an integrated sensing,communication and computation(ISCC)framework has been proposed,which is anticipated to be a key enabler in the era of 6G networks.Although the advantages of pushing intelligence to edge devices are multi-fold,some challenges arise when incorporating FL into wireless networks under the umbrella of ISCC.This paper provides a comprehensive survey of FL,with special emphasis on the design and optimization of ISCC.We commence by introducing the background and fundamentals of FL and the ISCC framework.Subsequently,the aforementioned challenges are highlighted and the state of the art in potential solutions is reviewed.Finally,design guidelines are provided for the incorporation of FL and ISCC.Overall,this paper aims to contribute to the understanding of FL in the context of wireless networks,with a focus on the ISCC framework,and provide insights into addressing the challenges and optimizing the design for the integration of FL into future 6G networks.

A Clustering-tree Topology Control Based on the Energy Forecast for Heterogeneous Wireless Sensor Networks

How to design an energy-efficient algorithm to maximize the network lifetime in complicated scenarios is a critical problem for heterogeneous wireless sensor networks(HWSN).In this paper, a clustering-tree topology control algorithm based on the energy forecast(CTEF) is proposed for saving energy and ensuring network load balancing, while considering the link quality, packet loss rate, etc. In CTEF, the average energy of the network is accurately predicted per round(the lifetime of the network is denoted by rounds) in terms of the difference between the ideal and actual average residual energy using central limit theorem and normal distribution mechanism, simultaneously. On this basis, cluster heads are selected by cost function(including the energy, link quality and packet loss rate) and their distance.The non-cluster heads are determined to join the cluster through the energy, distance and link quality. Furthermore, several noncluster heads in each cluster are chosen as the relay nodes for transmitting data through multi-hop communication to decrease the load of each cluster-head and prolong the lifetime of the network. The simulation results show the efficiency of CTEF. Compared with low-energy adaptive clustering hierarchy(LEACH), energy dissipation forecast and clustering management(EDFCM) and efficient and dynamic clustering scheme(EDCS)protocols, CTEF has longer network lifetime and receives more data packets at base station.

Improved Performance for a Heterogeneous Satellite-Cooperative Network with Best Relay Node Selection

Nowadays, hybrid satellite-terrestrial cooperative network has emerged as a key technology to provide a great variety of communication services. The deployment of this network will improve coverage and capacity in remote areas. Despite the benefits of this network, by increasing the number of users, communication efficiency based on interference management is a major challenge in satellite-based system. Also, the direct links between satellite system and the terrestrial equipment do not always have desirable channel condition. In order to avoid serious throughput degradation, choosing a cooperative relay node is very important. In this paper, Stackelberg game is exploited for interference management that is raised by satellites in down link over terrestrial equipment. Then, for interference management between ground station and relay node with other mobile users, CVX is used to allocate optimum power. Also, the best relay node in this structure is selected based on the harmonic mean function. Thus, the performance of the heterogeneous satellite-cooperative network is investigated based on three benchmarks, namely, successful transmission, energy consumption and outage probability. Finally, the simulation results showed the effect of proposed system model on the performance of next generation satellite networks.

Energy-Efficient User Association in Heterogeneous Networks with M2M/H2H Coexistence under QoS Guarantees

In this paper, we propose an energy efficient user association scheme for uplink heterogeneous networks with machine-to-machine(M2M) and human-to-human(H2H) coexistence. A group based random access protocol is designed for massive number of machine-typecommunications(MTC) user equipments'(UEs) transmissions. A user association problem for UEs' energy efficiency maximization is formulated considering the HTC UEs' quality of service(QoS) guarantees and load balance among multiple BSs, simultaneously. A distributed iterative algorithm is developed to solve the optimization problem. In addition, the convergence of the proposed algorithm is proved. Simulation results show that our proposed scheme outperforms other schemes in terms of energy efficiency and QoS guarantees.

Hierarchical Cooperative Control of Connected Vehicles:From Heterogeneous Parameters to Heterogeneous Structures

As one of the typical applications of connected vehicles(CVs),the vehicle platoon control technique has been proven to have the advantages of reducing emissions,improving traffic throughout and driving safety.In this paper,a unified hierarchical framework is designed for cooperative control of CVs with both heterogeneous model parameters and structures.By separating neighboring information interaction from local dynamics control,the proposed framework is designed to contain an upper-level observing layer and a lower-level tracking control layer,which helps address the heterogeneity in vehicle parameters and structures.Within the proposed framework,an observer is designed for following vehicles to observe the leading vehicle's states using neighboring communication,while a tracking controller is designed to track the observed leading vehicle using local feedback control.Closed-loop stability in the absence and presence of communication time delay is analyzed,and the observer is further extended to a finite time convergent one to address string stability under general communication topology.Numerical simulation and field experiment verify the effectiveness of the proposed method.

High Capacity Data Rate System:Review of Visible Light Communications Technology

Wireless communications have become an integral part of global convergence as global connectedness has gradually become dependent on its efficient deployment.The need for"more-broadband"techniques in relation to the ever increasing growth rate of the data hungry society now necessitates novel techniques for the high-speed data transmission.While advancements have been made in this regard,the projection of having an eventual Internet of everything (IoE) deployment will result in an unimaginable transmission data rate requirement as huge data traffic will be conveyed per time within the communications network,which will require a capacity upgrade of the existing infrastructure.Visible light communications (VLCs),as an integral part of optical wireless communications (OWCs),have been reviewed in this article,having the capacity to extend the achievable data rate requirement of the wireless communications network.The technologies,techniques,and best practices have been presented alongside technology integration for the seamless high capacity wireless broadband deployment.

Green Air-Ground Integrated Heterogeneous Network in 6G Era

The research of three-dimensional integrated communication technology plays a key role in achieving the ubiquitous connectivity,ultra-high data rates,and emergency communications in the sixth generation(6G)networks.Aerial networking provides a prom⁃ising solution to flexible,scalable,low-cost and reliable coverage for wireless devices.The integration of aerial network and terrestrial network has been an inevitable paradigm in the 6G era.However,energy-efficient communications and networking among aerial net⁃work and terrestrial network face great challenges.This paper is dedicated to discussing green communications of the air-ground integrated heterogeneous network(AGIHN).We first provide a brief introduction to the characteristics of AGIHN in 6G networks.Further,we analyze the challenges of green AGIHN from the aspects of green terrestrial networks and green aerial networks.Finally,several solutions to and key technologies of the green AGIHN are discussed.

Single-cell analysis of cellular heterogeneity and interactions in the ischemia-reperfusion injured mouse intestine

Nine major cell populations among 46,716 cells were identified in mouse intestinal ischemia‒reperfusion(II/R)injury by single-cell RNA sequencing.For enterocyte cells,11 subclusters were found,in which enterocyte cluster 1(EC1),enterocyte cluster 3(EC3),and enterocyte cluster 8(EC8)were newly discovered cells in ischemia 45 min/reperfusion 720 min(I 45 min/R 720 min)group.EC1 and EC3 played roles in digestion and absorption,and EC8 played a role in cell junctions.For TA cells,after ischemia 45 min/reperfusion 90 min(I 45 min/R 90 min),many TA cells at the stage of proliferation were identified.For Paneth cells,Paneth cluster 3 was observed in the resting state of normal jejunum.After I 45 min/R 90 min,three new subsets were found,in which Paneth cluster 1 had good antigen presentation activity.The main functions of goblet cells were to synthesize and secrete mucus,and a novel subcluster(goblet cluster 5)with highly proliferative ability was discovered in I 45 min/R 90 min group.As a major part of immune system,the changes in T cells with important roles were clarified.Notably,enterocyte cells secreted Guca2b to interact with Gucy2c receptor on the membranes of stem cells,TA cells,Paneth cells,and goblet cells to elicit intercellular communication.One marker known as glutathione S-transferase mu 3(GSTM3)affected intestinal mucosal barrier function by adjusting mitogen-activated protein kinases(MAPK)signaling during II/R injury.The data on the heterogeneity of intestinal cells,cellular communication and the mechanism of GSTM3 provide a cellular basis for treating II/R injury.

Mobile-Service Based Max-Min Fairness Resource Scheduling for Heterogeneous Vehicular Networks

This paper investigates the resource scheduling for heterogeneous vehicular networks, where some moving vehicles are selected and scheduled as helping relays to assist information transmission between the roadside infrastructure and other moving vehicles. For such a system, we propose a mobile-service based max-min fairness resource scheduling scheme, where service amount which is more suitable for high mobility scenarios is adopted to characterize the information transmission capacity of the links and the max-min criteria is adopted to meet the fairness requirement of the moving vehicles. Simulation results demonstrate the effectiveness of our proposed scheme. It is shown that our proposed scheme archives higher throughput and better fairness compared with random scheduling scheme and non-relaying scheme.

Balancing D2D Communication Relayed Traffic Offloading in Multi-Tier HetNets

In Heterogeneous Networks (HetNets), Integrating Device-to-Device communication (D2D) techniques presents as a promising solution for improving system performance by offloading traffic from heavily loaded macro cell (MC) to small cells (SCs). For instance, D2D can be used to offload traffic from heavily-loaded cells to light-loaded small cells. However, offloading new users may result in an unfair load distribution among small cells and consequently may affect the quality of service of some users. To achieve better performance and reduce blocking probability load balancing among small cells should be considered when we offload traffic from macro to small cells. In this paper, we consider a centralized offloaded relay selection scheme, in which a cellular provider can decide whether users can assist each other to relay their traffic to small cells. We propose a joint user-relay selection with dynamic load balancing scheme based on D2D communications using the Kuhn-Munkres (K-M) method. The offloading process considers the load from MC to SCs and among SCs. Compared to previous works, our simulation results show that the proposed scheme increases the number of admitted users in the system, and achieves a higher load balancing fairness index among small cells. Also, our scheme achieves a higher rate fairness index among users by adjusting the signal to interference plus noise ratio (SINR) threshold.

Distributed Heterogeneous Multi-Agent Optimization with Stochastic Sub-Gradient

This paper studies the optimization problem of heterogeneous networks under a timevarying topology.Each agent only accesses to one local objective function,which is nonsmooth.An improved algorithm with noisy measurement of local objective functions' sub-gradients and additive noises among information exchanging between each pair of agents is designed to minimize the sum of objective functions of all agents.To weaken the effect of these noises,two step sizes are introduced in the control protocol.By graph theory,stochastic analysis and martingale convergence theory,it is proved that if the sub-gradients are uniformly bounded,the sequence of digraphs is balanced and the union graph of all digraphs is joint strongly connected,then the designed control protocol can force all agents to find the global optimal point almost surely.At last,the authors give some numerical examples to verify the effectiveness of the stochastic sub-gradient algorithms.

Multi-radio access based bandwidth allocation strategy for video communication in heterogeneous wireless networks

In order to make full use of the radio resource of heterogeneous wireless networks（HWNs） and promote the quality of service（Qo S） of multi-homing users for video communication, a bandwidth allocation algorithm based on multi-radio access is proposed in this paper. The proposed algorithm adopts an improved distributed common radio resource management（DCRRM） model which can reduce the signaling overhead sufficiently. This scheme can be divided into two phases. In the first phase, candidate network set of each user is obtained according to the received signal strength（RSS）. And the simple additive weighted（SAW） method is employed to determine the active network set. In the second phase, the utility optimization problem is formulated by linear combining of the video communication satisfaction model, cost model and energy efficiency model. And finding the optimal bandwidth allocation scheme with Lagrange multiplier method and Karush-Kuhn-Tucker（KKT） conditions. Simulation results show that the proposed algorithm promotes the network load performances and guarantees that users obtain the best joint utility under current situation.

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.