Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although...Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.展开更多
In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increase...In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.展开更多
As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from bo...As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.展开更多
Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired ...Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired power deliveries applica-tions today,just like what happened to wireless communica-tion nowadays.Over the years,WPT has become more mature and more wirelessly charged or powered products have become available on the market.This mini review intends to summarize recent breakthroughs in WPT inte-grated circuits(IC)research.展开更多
This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design co...This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.展开更多
The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few hav...The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.展开更多
This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding type...This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.展开更多
This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable th...This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.展开更多
The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industri...The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.展开更多
Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacki...Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,simulation results verify the effectiveness of the proposed algorithms.展开更多
Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present ...Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.展开更多
In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET...In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.展开更多
With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated...With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.展开更多
To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-ne...To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.展开更多
Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor ...Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxygen level,body motion,and so on.They sense the data and communicate it to the Body Area Network(BAN)Coordinator.The main challenge for the WBAN is energy consumption.These issues can be addressed by implementing an effective Medium Access Control(MAC)protocol that reduces energy consumption and increases network lifetime.The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard.In our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the data.We gave priority to the highly critical data to get the Guarantee Tine Slots(GTS)in IEEE 802.15.4 standard superframe to achieve greater energy efficiency.The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity.As an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing MAC protocols,the MVDR performed very well with low energy intake,less interruption,and an enhanced packet-sharing ratio.展开更多
Energy conservation has become a significant consideration in wireless sensor networks(WSN).In the sensor network,the sensor nodes have internal batteries,and as a result,they expire after a certain period.As a result,...Energy conservation has become a significant consideration in wireless sensor networks(WSN).In the sensor network,the sensor nodes have internal batteries,and as a result,they expire after a certain period.As a result,expanding the life duration of sensing devices by improving data depletion in an effective and sustainable energy-efficient way remains a challenge.Also,the clustering strategy employs to enhance or extend the life cycle of WSNs.We identify the supervisory head node(SH)or cluster head(CH)in every grouping considered the feasible strategy for power-saving route discovery in the clustering model,which diminishes the communication overhead in the WSN.However,the critical issue was determining the best SH for ensuring timely communication services.Our secure and energy concise route revamp technology(SECRET)protocol involves selecting an energy-concise cluster head(ECH)and route revamping to optimize navigation.The sensors transmit information over the ECH,which delivers the information to the base station via the determined optimal path using our strategy for effective data transmission.We modeled our methods to accom-plish power-efficient multi-hop routing.Furthermore,protected navigation helps to preserve energy when routing.The suggested solution improves energy savings,packet delivery ratio(PDR),route latency(RL),network lifetime(NL),and scalability.展开更多
While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas...While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas,few studies focus on the fundamental modeling and related design automation of receiver systems.This article reviews the development of MWPT and MWEH receivers,with a focus on rectenna design automation.A novel rectifier model capable of accurately modeling the rectification process under both high and low input power is presented.The model reveals the theoretical boundary of radio frequency-to-direct current(dc)power conversion efficiency and,most importantly,enables an automated system design.The automated rectenna design flow is sequential,with the minimal engagement of iterative optimization.It covers the design automation of every module(i.e.,rectifiers,matching circuits,antennae,and dc–dc converters).Scaling-up of the technique to large rectenna arrays is also possible,where the challenges in array partitioning and power combining are briefly discussed.In addition,several cutting-edge rectenna techniques for MWPT and MWEH are reviewed,including the dynamic range extension technique,the harmonics-based retro-directive technique,and the simultaneous wireless information and power transfer technique,which can be good complements to the presented automated design methodology.展开更多
In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of u...In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.展开更多
In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in...In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in such a network is the localization of underwater nodes.Localization is required for tracking objects and detecting the target.It is also considered tagging of data where sensed contents are not found of any use without localization.This is useless for application until the position of sensed content is confirmed.This article’s major goal is to review and analyze underwater node localization to solve the localization issues in UWSN.The present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes underwater.Also,a detailed subdivision of these localization schemes is given.Further,these localization schemes are compared from different perspectives.The detailed analysis of these schemes in terms of certain performance metrics has been discussed in this paper.At the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.展开更多
Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although g...Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although great efforts have been made to explore the effectiveness of different AI models,it is still an open problem whether these models,trained with the data collected from all base stations(BSs),could work when some BSs are unavailable.In this paper,we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work.Particularly,a Siamese Network based Wireless Positioning Model(SNWPM)is proposed to predict the location of mobile user equipment from channel state information(CSI)collected from 5G BSs.Furthermore,a Feature Aware Attention Module(FAAM)is introduced to reinforce the capability of feature extraction from CSI data.Experiments are conducted on the 2022 Wireless Communication AI Competition(WAIC)dataset.The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable.Compared with other AI models,the proposed SNWPM can reduce the positioning error by nearly 50%to more than 60%while using less parameters and lower computation resources.展开更多
基金supported by the National Natural Science Foundation of China 62001051.
文摘Wireless Power Transfer(WPT)technology can provide real-time power for many terminal devices in Internet of Things(IoT)through millimeterWave(mmWave)to support applications with large capacity and low latency.Although the intelligent reflecting surface(IRS)can be adopted to create effective virtual links to address the mmWave blockage problem,the conventional solutions only adopt IRS in the downlink from the Base Station(BS)to the users to enhance the received signal strength.In practice,the reflection of IRS is also applicable to the uplink to improve the spectral efficiency.It is a challenging to jointly optimize IRS beamforming and system resource allocation for wireless energy acquisition and information transmission.In this paper,we first design a Low-Energy Adaptive Clustering Hierarchy(LEACH)clustering protocol for clustering and data collection.Then,the problem of maximizing the minimum system spectral efficiency is constructed by jointly optimizing the transmit power of sensor devices,the uplink and downlink transmission times,the active beamforming at the BS,and the IRS dynamic beamforming.To solve this non-convex optimization problem,we propose an alternating optimization(AO)-based joint solution algorithm.Simulation results show that the use of IRS dynamic beamforming can significantly improve the spectral efficiency of the system,and ensure the reliability of equipment communication and the sustainability of energy supply under NLOS link.
基金supported by Priority Research Centers Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education,Science and Technology(2018R1A6A1A03024003)the MSIT(Ministry of Science and ICT),Korea,under the Innovative Human Resource Development for Local Intellectualization support program(IITP-2023-2020-0-01612)supervised by the IITP(Institute for Information&communications TechnologyPlanning&Evaluation).
文摘In industrial wireless networks,data transmitted from source to destination are highly repetitive.This often leads to the queuing of the data,and poor management of the queued data results in excessive delays,increased energy consumption,and packet loss.Therefore,a nature-inspired-based Dragonfly Interaction Optimization Algorithm(DMOA)is proposed for optimization of the queue delay in industrial wireless networks.The term“interaction”herein used is the characterization of the“flying movement”of the dragonfly towards damselflies(female dragonflies)for mating.As a result,interaction is represented as the flow of transmitted data packets,or traffic,from the source to the base station.This includes each and every feature of dragonfly movement as well as awareness of the rival dragonflies,predators,and damselflies for the desired optimization of the queue delay.These features are juxtaposed as noise and interference,which are further used in the calculation of industrial wireless metrics:latency,error rate(reliability),throughput,energy efficiency,and fairness for the optimization of the queue delay.Statistical analysis,convergence analysis,the Wilcoxon test,the Friedman test,and the classical as well as the 2014 IEEE Congress of Evolutionary Computation(CEC)on the benchmark functions are also used for the evaluation of DMOA in terms of its robustness and efficiency.The results demonstrate the robustness of the proposed algorithm for both classical and benchmarking functions of the IEEE CEC 2014.Furthermore,the accuracy and efficacy of DMOA were demonstrated by means of the convergence rate,Wilcoxon testing,and ANOVA.Moreover,fairness using Jain’s index in queue delay optimization in terms of throughput and latency,along with computational complexity,is also evaluated and compared with other algorithms.Simulation results show that DMOA exceeds other bio-inspired optimization algorithms in terms of fairness in queue delay management and average packet loss.The proposed algorithm is also evaluated for the conflicting objectives at Pareto Front,and its analysis reveals that DMOA finds a compromising solution between the objectives,thereby optimizing queue delay.In addition,DMOA on the Pareto front delivers much greater performance when it comes to optimizing the queuing delay for industry wireless networks.
基金National Natural Science Foundation of China(Grant No.62101138)Shandong Natural Science Foundation(Grant No.ZR2021QD148)+1 种基金Guangdong Natural Science Foundation(Grant No.2022A1515012573)Guangzhou Basic and Applied Basic Research Project(Grant No.202102020701)for providing funds for publishing this paper。
文摘As positioning sensors,edge computation power,and communication technologies continue to develop,a moving agent can now sense its surroundings and communicate with other agents.By receiving spatial information from both its environment and other agents,an agent can use various methods and sensor types to localize itself.With its high flexibility and robustness,collaborative positioning has become a widely used method in both military and civilian applications.This paper introduces the basic fundamental concepts and applications of collaborative positioning,and reviews recent progress in the field based on camera,LiDAR(Light Detection and Ranging),wireless sensor,and their integration.The paper compares the current methods with respect to their sensor type,summarizes their main paradigms,and analyzes their evaluation experiments.Finally,the paper discusses the main challenges and open issues that require further research.
文摘Wireless power transfer(WPT)has been a popular topic in power integrated circuit(IC)designs in the past decade.As slogan"cutting the last wire"presented in ISSCC’15[1],WPT is poised to take over many wired power deliveries applica-tions today,just like what happened to wireless communica-tion nowadays.Over the years,WPT has become more mature and more wirelessly charged or powered products have become available on the market.This mini review intends to summarize recent breakthroughs in WPT inte-grated circuits(IC)research.
基金the NSF CCSS-2152638 and the IEN Center Grant from the Institute for Electronics and Nanotechnology at Georgia Tech.
文摘This review summarizes recent progress in developing wireless,batteryless,fully implantable biomedical devices for real-time continuous physiological signal monitoring,focusing on advancing human health care.Design considerations,such as biological constraints,energy sourcing,and wireless communication,are discussed in achieving the desired performance of the devices and enhanced interface with human tissues.In addition,we review the recent achievements in materials used for developing implantable systems,emphasizing their importance in achieving multi-functionalities,biocompatibility,and hemocompatibility.The wireless,batteryless devices offer minimally invasive device insertion to the body,enabling portable health monitoring and advanced disease diagnosis.Lastly,we summarize the most recent practical applications of advanced implantable devices for human health care,highlighting their potential for immediate commercialization and clinical uses.
文摘The structural optimization of wireless sensor networks is a critical issue because it impacts energy consumption and hence the network’s lifetime.Many studies have been conducted for homogeneous networks,but few have been performed for heterogeneouswireless sensor networks.This paper utilizes Rao algorithms to optimize the structure of heterogeneous wireless sensor networks according to node locations and their initial energies.The proposed algorithms lack algorithm-specific parameters and metaphorical connotations.The proposed algorithms examine the search space based on the relations of the population with the best,worst,and randomly assigned solutions.The proposed algorithms can be evaluated using any routing protocol,however,we have chosen the well-known routing protocols in the literature:Low Energy Adaptive Clustering Hierarchy(LEACH),Power-Efficient Gathering in Sensor Information Systems(PEAGSIS),Partitioned-based Energy-efficient LEACH(PE-LEACH),and the Power-Efficient Gathering in Sensor Information Systems Neural Network(PEAGSIS-NN)recent routing protocol.We compare our optimized method with the Jaya,the Particle Swarm Optimization-based Energy Efficient Clustering(PSO-EEC)protocol,and the hybrid Harmony Search Algorithm and PSO(HSA-PSO)algorithms.The efficiencies of our proposed algorithms are evaluated by conducting experiments in terms of the network lifetime(first dead node,half dead nodes,and last dead node),energy consumption,packets to cluster head,and packets to the base station.The experimental results were compared with those obtained using the Jaya optimization algorithm.The proposed algorithms exhibited the best performance.The proposed approach successfully prolongs the network lifetime by 71% for the PEAGSIS protocol,51% for the LEACH protocol,10% for the PE-LEACH protocol,and 73% for the PEGSIS-NN protocol;Moreover,it enhances other criteria such as energy conservation,fitness convergence,packets to cluster head,and packets to the base station.
基金supported in part by the National Natural Science Foundation of China(Nos.62071441 and 61701464)in part by the Fundamental Research Funds for the Central Universities(No.202151006).
文摘This study explores the application of single photon detection(SPD)technology in underwater wireless optical communication(UWOC)and analyzes the influence of different modulation modes and error correction coding types on communication performance.The study investigates the impact of on-off keying(OOK)and 2-pulse-position modulation(2-PPM)on the bit error rate(BER)in single-channel intensity and polarization multiplexing.Furthermore,it compares the error correction performance of low-density parity check(LDPC)and Reed-Solomon(RS)codes across different error correction coding types.The effects of unscattered photon ratio and depolarization ratio on BER are also verified.Finally,a UWOC system based on SPD is constructed,achieving 14.58 Mbps with polarization OOK multiplexing modulation and 4.37 Mbps with polarization 2-PPM multiplexing modulation using LDPC code error correction.
基金supported by National Natural Science Foundation of China(No.61901229 and No.62071242)the Project of Jiangsu Engineering Research Center of Novel Optical Fiber Technology and Communication Network(No.SDGC2234)+1 种基金the Open Research Project of Jiangsu Provincial Key Laboratory of Photonic and Electronic Materials Sciences and Technology(No.NJUZDS2022-008)the Post-Doctoral Research Supporting Program of Jiangsu Province(No.SBH20).
文摘This paper investigates a wireless powered and backscattering enabled sensor network based on the non-linear energy harvesting model, where the power beacon(PB) delivers energy signals to wireless sensors to enable their passive backscattering and active transmission to the access point(AP). We propose an efficient time scheduling scheme for network performance enhancement, based on which each sensor can always harvest energy from the PB over the entire block except its time slots allocated for passive and active information delivery. Considering the PB and wireless sensors are from two selfish service providers, we use the Stackelberg game to model the energy interaction among them. To address the non-convexity of the leader-level problem, we propose to decompose the original problem into two subproblems and solve them iteratively in an alternating manner. Specifically, the successive convex approximation, semi-definite relaxation(SDR) and variable substitution techniques are applied to find a nearoptimal solution. To evaluate the performance loss caused by the interaction between two providers, we further investigate the social welfare maximization problem. Numerical results demonstrate that compared to the benchmark schemes, the proposed scheme can achieve up to 35.4% and 38.7% utility gain for the leader and the follower, respectively.
基金supported by the Key Project of Guizhou Science and Technology Support Program,Guizhou Key Science and Support[2021]-001supported by the Key Laboratory of Cognitive Radio and Information Processing,Ministry of Education(Guilin University of Electronic Technology)(CRKL220203)+2 种基金Key Laboratory of Middle Atmosphere and Global Environment Observation(LAGEO)Institute of Atmospheric Physics,Chinese Academy of Sciences(LAGEO-2022-02)Henan Province Key R&D and Promotion Special Project(No.212102210166)“Double First-Class”Discipline Creation Project of Surveying Science and Technology(GCCRC202306).
文摘The development of the fifth-generation(5G)mobile communication systems has entered the commercialization stage.5G has a high data rate,low latency,and high reliability that can meet the basic demands of most industries and daily life,such as the Internet of Things(IoT),intelligent transportation systems,positioning,and navigation.The continuous progress and development of society have aroused wide concern.Positioning accuracy is the core demand for the applications,especially in complex environments such as airports,warehouses,supermarkets,and basements.However,many factors also affect the accuracy of positioning in those environments,for example,multipath effects,non-line-of-sight,and clock synchronization errors.This paper provides a comprehensive review of the existing works about positioning for the future wireless network and discusses its key techniques and algorithms,as well as the current development and future directions.We first outline the current traditional positioning technologies and algorithms,which are discussed and analyzed with the relevant literature.In addition,we also discuss application scenarios for wireless localization.By comparing different positioning systems,the challenges and future development directions of existing wireless positioning systems are prospected.
基金supported by the National Natural Science Foundation of China(NSFC)(61831002,62001076)the General Program of Natural Science Foundation of Chongqing(No.CSTB2023NSCQ-MSX0726,No.cstc2020jcyjmsxmX0878).
文摘Wireless Sensor Network(WSN)is widely utilized in large-scale distributed unmanned detection scenarios due to its low cost and flexible installation.However,WSN data collection encounters challenges in scenarios lacking communication infrastructure.Unmanned aerial vehicle(UAV)offers a novel solution for WSN data collection,leveraging their high mobility.In this paper,we present an efficient UAV-assisted data collection algorithm aimed at minimizing the overall power consumption of the WSN.Firstly,a two-layer UAV-assisted data collection model is introduced,including the ground and aerial layers.The ground layer senses the environmental data by the cluster members(CMs),and the CMs transmit the data to the cluster heads(CHs),which forward the collected data to the UAVs.The aerial network layer consists of multiple UAVs that collect,store,and forward data from the CHs to the data center for analysis.Secondly,an improved clustering algorithm based on K-Means++is proposed to optimize the number and locations of CHs.Moreover,an Actor-Critic based algorithm is introduced to optimize the UAV deployment and the association with CHs.Finally,simulation results verify the effectiveness of the proposed algorithms.
文摘Large-scale wireless sensor networks(WSNs)play a critical role in monitoring dangerous scenarios and responding to medical emergencies.However,the inherent instability and error-prone nature of wireless links present significant challenges,necessitating efficient data collection and reliable transmission services.This paper addresses the limitations of existing data transmission and recovery protocols by proposing a systematic end-to-end design tailored for medical event-driven cluster-based large-scale WSNs.The primary goal is to enhance the reliability of data collection and transmission services,ensuring a comprehensive and practical approach.Our approach focuses on refining the hop-count-based routing scheme to achieve fairness in forwarding reliability.Additionally,it emphasizes reliable data collection within clusters and establishes robust data transmission over multiple hops.These systematic improvements are designed to optimize the overall performance of the WSN in real-world scenarios.Simulation results of the proposed protocol validate its exceptional performance compared to other prominent data transmission schemes.The evaluation spans varying sensor densities,wireless channel conditions,and packet transmission rates,showcasing the protocol’s superiority in ensuring reliable and efficient data transfer.Our systematic end-to-end design successfully addresses the challenges posed by the instability of wireless links in large-scaleWSNs.By prioritizing fairness,reliability,and efficiency,the proposed protocol demonstrates its efficacy in enhancing data collection and transmission services,thereby offering a valuable contribution to the field of medical event-drivenWSNs.
基金This work was supported in part by the open research fund of National Mobile Communications Research Laboratory,Southeast University(No.2023D11)in part by Sponsored by program for Science&Technology Innovation Talents in Universities of Henan Province(23HASTIT019)+2 种基金in part by Natural Science Foundation of Henan Province(20232300421097)in part by the project funded by China Postdoctoral Science Foundation(2020M682345)in part by the Henan Postdoctoral Foundation(202001015).
文摘In this paper,we investigate IRS-aided user cooperation(UC)scheme in millimeter wave(mmWave)wirelesspowered sensor networks(WPSN),where two single-antenna users are wireless powered in the wireless energy transfer(WET)phase first and then cooperatively transmit information to a hybrid access point(AP)in the wireless information transmission(WIT)phase,following which the IRS is deployed to enhance the system performance of theWET andWIT.We maximized the weighted sum-rate problem by jointly optimizing the transmit time slots,power allocations,and the phase shifts of the IRS.Due to the non-convexity of the original problem,a semidefinite programming relaxation-based approach is proposed to convert the formulated problem to a convex optimization framework,which can obtain the optimal global solution.Simulation results demonstrate that the weighted sum throughput of the proposed UC scheme outperforms the non-UC scheme whether equipped with IRS or not.
基金supported in part by National Natural Science Foundation of China under Grants 62122069, 62071431, 62072490 and 62301490in part by Science and Technology Development Fund of Macao SAR, China under Grant 0158/2022/A+2 种基金in part by the Guangdong Basic and Applied Basic Research Foundation (2022A1515011287)in part by MYRG202000107-IOTSCin part by FDCT SKL-IOTSC (UM)-2021-2023
文摘With the development of the Internet of Things(IoT),it requires better performance from wireless sensor networks(WSNs),such as larger coverage,longer lifetime,and lower latency.However,a large amount of data generated from monitoring and long-distance transmission places a heavy burden on sensor nodes with the limited battery power.For this,we investigate an unmanned aerial vehicles assisted mobile wireless sensor network(UAV-assisted WSN)to prolong the network lifetime in this paper.Specifically,we use UAVs to assist the WSN in collecting data.In the current UAV-assisted WSN,the clustering and routing schemes are determined sequentially.However,such a separate consideration might not maximize the lifetime of the whole WSN due to the mutual coupling of clustering and routing.To efficiently prolong the lifetime of the WSN,we propose an integrated clustering and routing scheme that jointly optimizes the clustering and routing together.In the whole network space,it is intractable to efficiently obtain the optimal integrated clustering and routing scheme.Therefore,we propose the Monte-Las search strategy based on Monte Carlo and Las Vegas ideas,which can generate the chain matrix to guide the algorithm to find the solution faster.Unnecessary point-to-point collection leads to long collection paths,so a triangle optimization strategy is then proposed that finds a compromise path to shorten the collection path based on the geometric distribution and energy of sensor nodes.To avoid the coverage hole caused by the death of sensor nodes,the deployment of mobile sensor nodes and the preventive mechanism design are indispensable.An emergency data transmission mechanism is further proposed to reduce the latency of collecting the latency-sensitive data due to the absence of UAVs.Compared with the existing schemes,the proposed scheme can prolong the lifetime of the UAVassisted WSN at least by 360%,and shorten the collection path of UAVs by 56.24%.
基金supported by 2023 Liaoning Provincial Department of Education Basic Research Project (General Project)(JYTMS20230815)。
文摘To solve the low power transfer efficiency and magnetic field leakage problems of cardiac pacemaker wireless powering, we proposed a wireless power supply system suitable for implanted cardiac pacemaker based on mu-negative(MNG) and mu-nearzero(MNZ) metamaterials. First, a hybrid metamaterial consisted of central MNG unit for magnetic field concentration and surrounding MNZ units for magnetic leakage shielding was established by theoretical calculation. Afterwards, the magnetic field distribution of wireless power supply system with MNG-MNZ metamaterial slab was acquired via finite element simulation and verified to be better than the distribution with conventional MNG slab deployed. Finally, an experimental platform of wireless power supply system was established with which power transfer experiment and system temperature rise experiment were conducted.Simulation and experimental results showed that the power transfer efficiency was improved from 44.44%,19.42%, 8.63% and 6.19% to 55.77%, 62.39%, 20.81%and 14.52% at 9.6 mm, 20 mm, 30 mm and 50 mm,respectively. The maximum SAR acquired by SAR simulation under human body environment was-7.14 dbm and maximum reduction of the magnetic field strength around the receiving coil was 2.82 A/m. The maximum temperature rise during 30min charging test was 3.85℃,and the safety requirements of human bodies were met.
文摘Wireless Body Area Network(WBAN)is a cutting-edge technology that is being used in healthcare applications to monitor critical events in the human body.WBAN is a collection of in-body and on-body sensors that monitor human physical parameters such as temperature,blood pressure,pulse rate,oxygen level,body motion,and so on.They sense the data and communicate it to the Body Area Network(BAN)Coordinator.The main challenge for the WBAN is energy consumption.These issues can be addressed by implementing an effective Medium Access Control(MAC)protocol that reduces energy consumption and increases network lifetime.The purpose of the study is to minimize the energy consumption and minimize the delay using IEEE 802.15.4 standard.In our proposed work,if any critical events have occurred the proposed work is to classify and prioritize the data.We gave priority to the highly critical data to get the Guarantee Tine Slots(GTS)in IEEE 802.15.4 standard superframe to achieve greater energy efficiency.The proposed MAC provides higher data rates for critical data based on the history and current condition and also provides the best reliable service to high critical data and critical data by predicting node similarity.As an outcome,we proposed a MAC protocol for Variable Data Rates(MVDR).When compared to existing MAC protocols,the MVDR performed very well with low energy intake,less interruption,and an enhanced packet-sharing ratio.
文摘Energy conservation has become a significant consideration in wireless sensor networks(WSN).In the sensor network,the sensor nodes have internal batteries,and as a result,they expire after a certain period.As a result,expanding the life duration of sensing devices by improving data depletion in an effective and sustainable energy-efficient way remains a challenge.Also,the clustering strategy employs to enhance or extend the life cycle of WSNs.We identify the supervisory head node(SH)or cluster head(CH)in every grouping considered the feasible strategy for power-saving route discovery in the clustering model,which diminishes the communication overhead in the WSN.However,the critical issue was determining the best SH for ensuring timely communication services.Our secure and energy concise route revamp technology(SECRET)protocol involves selecting an energy-concise cluster head(ECH)and route revamping to optimize navigation.The sensors transmit information over the ECH,which delivers the information to the base station via the determined optimal path using our strategy for effective data transmission.We modeled our methods to accom-plish power-efficient multi-hop routing.Furthermore,protected navigation helps to preserve energy when routing.The suggested solution improves energy savings,packet delivery ratio(PDR),route latency(RL),network lifetime(NL),and scalability.
基金supported by the Singapore Ministry of Education Academic Research Fund Tier 1。
文摘While sufficient review articles exist on inductive short-range wireless power transfer(WPT),long-haul microwave WPT(MWPT)for solar power satellites,and ambient microwave wireless energy harvesting(MWEH)in urban areas,few studies focus on the fundamental modeling and related design automation of receiver systems.This article reviews the development of MWPT and MWEH receivers,with a focus on rectenna design automation.A novel rectifier model capable of accurately modeling the rectification process under both high and low input power is presented.The model reveals the theoretical boundary of radio frequency-to-direct current(dc)power conversion efficiency and,most importantly,enables an automated system design.The automated rectenna design flow is sequential,with the minimal engagement of iterative optimization.It covers the design automation of every module(i.e.,rectifiers,matching circuits,antennae,and dc–dc converters).Scaling-up of the technique to large rectenna arrays is also possible,where the challenges in array partitioning and power combining are briefly discussed.In addition,several cutting-edge rectenna techniques for MWPT and MWEH are reviewed,including the dynamic range extension technique,the harmonics-based retro-directive technique,and the simultaneous wireless information and power transfer technique,which can be good complements to the presented automated design methodology.
基金supported in part by Shanghai Pujiang Program under Grant No.21PJ1402600in part by Natural Science Foundation of Chongqing,China under Grant No.CSTB2022NSCQ-MSX0375+4 种基金in part by Song Shan Laboratory Foundation,under Grant No.YYJC022022007in part by Zhejiang Provincial Natural Science Foundation of China under Grant LGJ22F010001in part by National Key Research and Development Program of China under Grant 2020YFA0711301in part by National Natural Science Foundation of China under Grant 61922049。
文摘In this paper,we investigate the minimization of age of information(AoI),a metric that measures the information freshness,at the network edge with unreliable wireless communications.Particularly,we consider a set of users transmitting status updates,which are collected by the user randomly over time,to an edge server through unreliable orthogonal channels.It begs a natural question:with random status update arrivals and obscure channel conditions,can we devise an intelligent scheduling policy that matches the users and channels to stabilize the queues of all users while minimizing the average AoI?To give an adequate answer,we define a bipartite graph and formulate a dynamic edge activation problem with stability constraints.Then,we propose an online matching while learning algorithm(MatL)and discuss its implementation for wireless scheduling.Finally,simulation results demonstrate that the MatL is reliable to learn the channel states and manage the users’buffers for fresher information at the edge.
文摘In recent years,there has been a rapid growth in Underwater Wireless Sensor Networks(UWSNs).The focus of research in this area is now on solving the problems associated with large-scale UWSN.One of the major issues in such a network is the localization of underwater nodes.Localization is required for tracking objects and detecting the target.It is also considered tagging of data where sensed contents are not found of any use without localization.This is useless for application until the position of sensed content is confirmed.This article’s major goal is to review and analyze underwater node localization to solve the localization issues in UWSN.The present paper describes various existing localization schemes and broadly categorizes these schemes as Centralized and Distributed localization schemes underwater.Also,a detailed subdivision of these localization schemes is given.Further,these localization schemes are compared from different perspectives.The detailed analysis of these schemes in terms of certain performance metrics has been discussed in this paper.At the end,the paper addresses several future directions for potential research in improving localization problems of UWSN.
基金supported by National Natural Science Foundation of China (No. 62076251)sponsored by IMT-2020(5G) Promotion Group 5G+AI Work Group+3 种基金jointly sponsored by China Academy of Information and Communications TechnologyGuangdong OPPO Mobile Telecommunications Corp., Ltdvivo Mobile Communication Co., LtdHuawei Technologies Co., Ltd
文摘Artificial intelligence(AI)models are promising to improve the accuracy of wireless positioning systems,particularly in indoor environments where unpredictable radio propagation channel is a great challenge.Although great efforts have been made to explore the effectiveness of different AI models,it is still an open problem whether these models,trained with the data collected from all base stations(BSs),could work when some BSs are unavailable.In this paper,we make the first effort to enhance the generalization ability of AI wireless positioning model to adapt to the scenario where only partial BSs work.Particularly,a Siamese Network based Wireless Positioning Model(SNWPM)is proposed to predict the location of mobile user equipment from channel state information(CSI)collected from 5G BSs.Furthermore,a Feature Aware Attention Module(FAAM)is introduced to reinforce the capability of feature extraction from CSI data.Experiments are conducted on the 2022 Wireless Communication AI Competition(WAIC)dataset.The proposed SNWPM achieves decimeter-level positioning accuracy even if the data of partial BSs are unavailable.Compared with other AI models,the proposed SNWPM can reduce the positioning error by nearly 50%to more than 60%while using less parameters and lower computation resources.
