Real-Time Monitoring System for Rotor Temperature of a Large Turbogenerator Based on SmartMesh IP Wireless Network Communication Technology

In this study,a real-time rotor temperature monitoring system for large turbogenerators using SmartMesh IP wireless network communication technology was designed and tested.The system is capable of providing comprehensive,accurate,continuous,and reliable real-time temperature monitoring for turbogenerators.Additionally,it has demonstrated satisfactory results in a real-time monitoring test of the rotor temperature of various famous large-scale turbogenerators and giant nuclear power half-speed turbogenerators designed and manufactured in China.The development and application of this wireless temperature measurement system would aid in improving the intelligent operation quality,safety,and stability of China’s large turbine generators and even the entire power system.

FLBS: Fuzzy lion Bayes system for intrusion detection in wireless communication network

An important problem in wireless communication networks (WCNs) is that they have a minimum number of resources, which leads to high-security threats. An approach to find and detect the attacks is the intrusion detection system (IDS). In this paper, the fuzzy lion Bayes system (FLBS) is proposed for intrusion detection mechanism. Initially, the data set is grouped into a number of clusters by the fuzzy clustering algorithm. Here, the Naive Bayes classifier is integrated with the lion optimization algorithm and the new lion naive Bayes (LNB) is created for optimally generating the probability measures. Then, the LNB model is applied to each data group, and the aggregated data is generated. After generating the aggregated data, the LNB model is applied to the aggregated data, and the abnormal nodes are identified based on the posterior probability function. The performance of the proposed FLBS system is evaluated using the KDD Cup 99 data and the comparative analysis is performed by the existing methods for the evaluation metrics accuracy and false acceptance rate (FAR). From the experimental results, it can be shown that the proposed system has the maximum performance, which shows the effectiveness of the proposed system in the intrusion detection.

Distribution algorithm of entangled particles for wireless quantum communication mesh networks

With ensured network connectivity in quantum channels, the issue of distributing entangled particles in wireless quantum communication mesh networks can be equivalently regarded as a problem of quantum backbone nodes selection in order to save cost and reduce complexity. A minimum spanning tree（ MST）-based quantum distribution algorithm（ QDMST） is presented to construct the mesh backbone network. First, the articulation points are found,and for each connected block uncovered by the articulation points, the general centers are solved. Then, both articulation points and general centers are classified as backbone nodes and an M ST is formed. The quantum path between every two neighbor nodes on the MST is calculated. The nodes on these paths are also classified as backbone nodes. Simulation results validate the advantages of QDMST in the average backbone nodes number and average quantum channel distance compared to the existing random selection algorithm under multiple network scenarios.

Distributed wireless quantum communication networks with partially entangled pairs

Wireless quantum communication networks transfer quantum state by teleportation. Existing research focuses on maximal entangled pairs. In this paper, we analyse the distributed wireless quantum communication networks with partially entangled pairs. A quantum routing scheme with multi-hop teleportation is proposed. With the proposed scheme, is not necessary for the quantum path to be consistent with the classical path. The quantum path and its associated classical path are established in a distributed way. Direct multi-hop teleportation is conducted on the selected path to transfer a quantum state from the source to the destination. Based on the feature of multi-hop teleportation using partially entangled pairs, if the node number of the quantum path is even, the destination node will add another teleportation at itself. We simulated the performance of distributed wireless quantum communication networks with a partially entangled state. The probability of transferring the quantum state successfully is statistically analyzed. Our work shows that multi-hop teleportation on distributed wireless quantum networks with partially entangled pairs is feasible.

Incentive Scheme for Slice Cooperation Based on D2D Communication in 5G Networks

In the 5th generation(5G)wireless communication networks,network slicing emerges where network operators(NPs)form isolated logical slices by the same cellular network infrastructure and spectrum resource.In coverage regions of access points(APs)shared by slices,device to device(D2D)communication can occur among different slices,i.e.,one device acts as D2D relay for another device serving by a different slice,which is defined as slice cooperation in this paper.Since selfish slices will not help other slices by cooperation voluntarily and unconditionally,this paper designs a novel resource allocation scheme to stimulate slice cooperation.The main idea is to encourage slice to perform cooperation for other slices by rewarding it with higher throughput.The proposed incentive scheme for slice cooperation is formulated by an optimal problem,where cooperative activities are introduced to the objective function.Since optimal solutions of the formulated problem are long term statistics,though can be obtained,a practical online slice scheduling algorithm is designed,which can obtain optimal solutions of the formulated maximal problem.Lastly,the throughput isolation indexes are defined to evaluate isolation performance of slice.According to simulation results,the proposed incentive scheme for slice cooperation can stimulate slice cooperation effectively,and the isolation of slice is also simulated and discussed.

Sum-Rate Maximization in Active RIS-Assisted Multi-Antenna WPCN

In this paper,we propose an active reconfigurable intelligent surface(RIS)enabled hybrid relaying scheme for a multi-antenna wireless powered communication network(WPCN),where the active RIS is employed to assist both wireless energy transfer(WET)from the power station(PS)to energyconstrained users and wireless information transmission(WIT)from users to the receiving station(RS).For further performance enhancement,we propose to employ both transmit beamforming at the PS and receive beamforming at the RS.We formulate a sumrate maximization problem by jointly optimizing the RIS phase shifts and amplitude reflection coefficients for both the WET and the WIT,transmit and receive beamforming vectors,and network resource allocation.To solve this non-convex problem,we propose an efficient alternating optimization algorithm with the linear minimum mean squared error criterion,semidefinite relaxation(SDR)and successive convex approximation techniques.Specifically,the tightness of applying the SDR is proved.Simulation results demonstrate that our proposed scheme with 10 reflecting elements(REs)and 4 antennas can achieve 17.78%and 415.48%performance gains compared to the single-antenna scheme with 10 REs and passive RIS scheme with 100 REs,respectively.

Maximum throughput design of wireless powered communication network with IRS-NOMA based on user clustering

A wireless powered communication network(WPCN)assisted by intelligent reflecting surface(IRS)is proposed in this paper,which can transfer information by non-orthogonal multiple access(NOMA)technology.In the system,in order to ensure that the hybrid access point(H-AP)can correctly decode user information via successive interference cancellation(SIC)technology,the information transmit power of user needs to satisfy a certain threshold,so as to meet the corresponding SIC constraints.Therefore,when the number of users who transfer information simultaneously increases,the system performance will be greatly restricted.To minimize the influence of SIC constraints on system performance,users are firstly clustered,and then each cluster collects energy from H-AP and finally,users transfer information based on NOMA with the assistance of IRS.Specifically,this paper aims to maximize the sum throughput of the system by jointly optimizing the beamforming of IRS and resource allocation of the system.The semi-definite relaxation(SDR)algorithm is employed to alternately optimize the beamforming of IRS in each time slot,and the joint optimization problem about user’s transmit power and time is transformed into two optimal time allocation sub-problems.The numerical results show that the proposed optimization scheme can effectively improve the sum throughput of the system.In addition,the results in the paper further reveals the positive impact of IRS on improving the sum throughput of the system.

Intelligent Decision Making Framework for 6G Network

Sixth Generation(6G)wireless communication network has been expected to provide global coverage,enhanced spectral efficiency,and AI(Artificial Intelligence)-native intelligence,etc.To meet these requirements,the computational concept of Decision-Making of cognition intelligence,its implementation framework adapting to foreseen innovations on networks and services,and its empirical evaluations are key techniques to guarantee the generationagnostic intelligence evolution of wireless communication networks.In this paper,we propose an Intelligent Decision Making(IDM)framework,acting as the role of network brain,based on Reinforcement Learning modelling philosophy to empower autonomous intelligence evolution capability to 6G network.Besides,usage scenarios and simulation demonstrate the generality and efficiency of IDM.We hope that some of the ideas of IDM will assist the research of 6G network in a new or different light.

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.

Throughput Maximization for Multi-UAV Enabled Millimeter Wave WPCN: Joint Time and Power Allocation

In this paper,we investigate the effective deployment of millimeter wave(mmWave)in unmanned aerial vehicle(UAV)-enabled wireless powered communication network(WPCN).In particular,a novel framework for optimizing the performance of such UAV-enabled WPCN in terms of system throughput is proposed.In the considered model,multiple UAVs monitor in the air along the scheduled flight trajectory and transmit monitoring data to micro base stations(mBSs)with the harvested energy via mmWave.In this case,we propose an algorithm for jointly optimizing transmit power and energy transfer time.To solve the non-convex optimization problem with tightly coupled variables,we decouple the problem into more tractable subproblems.By leveraging successive convex approximation(SCA)and block coordinate descent techniques,the optimal solution is obtained by designing a two-stage joint iteration optimization algorithm.Simulation results show that the proposed algorithm with joint transmit power and energy transfer time optimization achieves significant performance gains over Q-learning method and other benchmark schemes.

Energy intake,metabolic homeostasis,and human health

The energy substances(mainly carbohydrates and fats)are the basis and guarantee of life activity,especially the oxidative phosphorylation for energy supply.However,excessive absorption and accumulation of these substances can lead to metabolic diseases such as obesity,hyperlipidemia,diabetes,and cancers.A large amount of studies demonstrate that G protein-coupled receptors(GPCRs)play a key role in identification and absorption of energy substances,and the signaling network of nerves,immune,and endocrine regulates their storage and utilization.The gastrointestinal mucus layer not only identifies these substances through identification in diet components but also transfers immune,metabolic,and endocrine signals of hormones,cytokines,and chemokines by promoting interactions between receptors and ligands.These signaling molecules are transferred to corresponding organs,tissues,and cells by the circulatory system,and cell activity is regulated by amplifying of cell signals that constitute the wireless communication network among cells in the body.Absorption,accumulation,and utilization of energy substances in the body obey the law of energy conservation.Energy is stored in the form of fat,and meets the demand of body via two coupled mechanisms:catabolism and oxidative phosphorylation.Under normal physiological conditions,fat consumption involves ketone body metabolism through the circulatory system and glucose consumption requires blood lactic acid cycle.Accumulation of excessive energy leads to the abnormal activation of mammalian target of rapamycin(mTOR),thus promoting the excretion of glucose or glycogen in the form of blood glucose and urine glucose.Alternatively,the body cancels the intercellular contact inhibition and promotes cell proliferation to induce carcinogenesis,which can induce the consumption of large amounts of glucose.Intercellular communication is performed by signaling molecules via sensing,absorption,accumulation,and utilization of energy substances,and anabolism and catabolism are controlled by the central metabolic pathway.Therefore,slower catabolism will result in longer life expectancy,whereas faster catabolism results in shorter life expectancy.Energy substances in diet influence the balance between energy and metabolism in the body through the sensing function of the gastrointestinal system at two levels:cellular communication network and metabolic network.The present review of studies aims to strengthen our knowledge on cellular communication and metabolic networks to offer a dietary guidance on the metabolism and communication role of various foods.

Efficient Approach for Resource Allocation in WPCN Using Hybrid Optimization

The recent aggrandizement of radio frequency(RF)signals in wireless power transmission combined with energy harvesting methods have led to the replacement of traditional battery-powered wireless networks since the blooming RF technology provides energy renewal of wireless devices with the quality of service(QoS).In addition,it does not require any unnecessary alterations on the transmission hardware side.A hybridized global optimization technique uniting Global best and Local best(GL)based particle swarm optimization(PSO)and ant colony optimization(ACO)is proposed in this paper to optimally allocate resources in wireless powered communication networks(WPCN)through coordinated operation of communication groups,in which the wireless energy transfer and information sharing take place concomitantly by the aid of a cooperative relay positioned in between the communicating groups.The designed algorithm assists in minimizing power consumption and maximizes the weighted sum rate at the end-user side.Thus the principal target of the system is coordinated optimization of energy beamforming along with time and energy allocation to reduce the total energy consumed combined with assured information rates of the communication groups.Numerical outputs are presented to manifest the proposed system’s performance to verify the analytical results via simulations.

True-data testbed for 5G/B5G intelligent network

Future beyond fifth-generation(B5G)and sixth-generation(6G)mobile communications will shift from facilitating interpersonal communications to supporting internet of everything(IoE),where intelligent communications with full integration of big data and artificial intelligence(AI)will play an important role in improving network efficiency and providing high-quality service.As a rapid evolving paradigm,the AI-empowered mobile communications demand large amounts of data acquired from real network environment for systematic test and verification.Hence,we build the world’s first true-data testbed for 5G/B5G intelligent network(TTIN),which comprises 5G/B5G on-site experimental networks,data acquisition&data warehouse,and AI engine&network optimization.In the TTIN,true network data acquisition,storage,standardization,and analysis are available,which enable system-level online verification of B5G/6G-orientated key technologies and support data-driven network optimization through the closed-loop control mechanism.This paper elaborates on the system architecture and module design of TTIN.Detailed technical specifications and some of the established use cases are also showcased.

Maximum throughput design for IRS aided WPCN system based on NOMA

This paper considers a wireless powered communication network(WPC network, WPCN) based on non-orthogonal multiple access(NOMA) technology aided by intelligent reflective surfaces(IRS). WPCN mainly focuses on downlink energy transfer(ET) and uplink information transmission(IT). At the ET phase, a dedicated multi-antenna power station(PS) is equipped to supply power to users with the assistance of IRS, and at the IT phase, the IRS adjusts the phase to assist the user in applying NOMA technology to transmit information to the base station(BS), thus minimizing the impact of dynamic IRS on the system. Based on the above settings, the maximization of sum-throughput of the system under this working mode is studied. Due to the non-convexity of maximization problem of the sum-throughput of this system, block coordinate descent(BCD) technology is applied for alternative optimization of each system block by semidefinite relaxation(SDR) and particle swarm optimization(PSO) respectively. The numerical results show that compared with baseline scheme, the proposed optimization scheme can provide greater sum-throughput of the system.

Energy efficient data collection in UAV-assisted Internet of things:trajectory planning and aerodynamic-based attitude control

Due to its inherent characteristics of flexible mobility,unmanned aerial vehicle(UAV) is exploited as a cost-efficient mobile platform to assist remote data collection in the 5 th generation or beyond the 5 th generation(5 G/B5 G) wireless systems.Compared with static terrestrial base stations,the line-of-sight(LoS) link between UAVs and ground nodes are stronger due to their flexibility in three-dimensional(3 D) space.Due to the fact that flexible mobility of UAVs requires high propulsion power,the limited on-board energy constrains the performance of UAV-assisted data collection.It is worth noting that UAVs can be categorized into rotary-wing UAVs and fixed-wing UAVs,either has its own characteristics in propulsion energy consumption.In this article,a comprehensive review of state-of-art studies on trajectory design schemes for rotary-wing UAVs,as well as aerodynamic-aware attitude control strategies for fixed-wing UAVs was provided.Then,two case studies for energy-efficient data collection using rotary-wing UAVs and fixed-wing UAVs were presented,respectively.More specifically,an age-energy aware data collection scheme was demonstrated for rotary-wing UAVs to optimize the timeliness of collected data.Moreover,an aerodynamic-aware attitude control strategy for fixed-wing UAVs was also demonstrated under data collection requirements.