Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G t...Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access(NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying(CNAR) system for 5G is proposed by enabling the collaboration of source-relay(S-R) and relay-destination(R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR(S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.展开更多
IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment sc...IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment scenarios,the potentially high packet collision rate significantly decreases the communication efficiency of WLAN.In this paper,we propose an adaptive STA grouping scheme to overcome this dense network challenge in IEEE 802.11ax by using Buffer State Report(BSR)based Two-stage Mechanism(BTM).In order to achieve the optimal efficiency of BSR delivery,we analyze the functional relationship between STA number in group and Resource Unit(RU)efficiency.Based on this analysis results,an adaptive STA grouping algorithm with variable group size is proposed to achieve efficient grouping in BTM.The numerical results demonstrate that the proposed adaptive BTM grouping algorithm significantly improves the BSR delivery efficiency and the throughput of overall system and each STA in the ultra-dense wireless network.展开更多
A vertical carbon nanotube field-effect transistor(CNTFET) based on silicon(Si) substrate has been proposed and simulated using a semi-classical theory. A single-walled carbon nanotube(SWNT) and an n-type Si nanowire ...A vertical carbon nanotube field-effect transistor(CNTFET) based on silicon(Si) substrate has been proposed and simulated using a semi-classical theory. A single-walled carbon nanotube(SWNT) and an n-type Si nanowire in series construct the channel of the transistor. The CNTFET presents ambipolar characteristics at positive drain voltage(Vd) and n-type characteristics at negative Vd. The current is significantly influenced by the doping level of n-Si and the SWNT band gap. The n-branch current of the ambipolar characteristics increases with increasing doping level of the n-Si while the p-branch current decreases. The SWNT band gap has the same influence on the p-branch current at a positive Vd and n-type characteristics at negative Vd. The lower the SWNT band gap, the higher the current. However, it has no impact on the n-branch current in the ambipolar characteristics. Thick oxide is found to significantly degrade the current and the subthreshold slope of the CNTFETs.展开更多
Very few materials show large magnetoresistance(MR)under a low magnetic field at room temperature,which causes the barrier to the development of magnetic field sensors for detecting low-level electromagnetic radiation...Very few materials show large magnetoresistance(MR)under a low magnetic field at room temperature,which causes the barrier to the development of magnetic field sensors for detecting low-level electromagnetic radiation in real-time.Here,a hybrid reduced graphene oxide(rGO)-based magnetic field sensor is produced by in situ deposition of FeCo nanoparticles(NPs)on reduced graphene oxide(rGO).Special quantum magnetoresistance(MR)of the hybrid rGO is observed,which unveils that Abrikosov's quantum model for layered materials can occur in hybrid rGO;meanwhile,the MR value can be tunable by adjusting the particle density of FeCo NPs on rGO nanosheets.Very high MR value up to 21.02±5.74%at 10 kOe at room temperature is achieved,and the average increasing rate of resistance per kOe is up to 0.9282ΩkOe^-1.In this paper,we demonstrate that the hybrid rGO-based magnetic field sensor can be embedded in a wireless system for real-time detection of low-level electromagnetic radiation caused by a working mobile phone.We believe that the two-dimensional nanomaterials with controllable MR can be integrated with a wireless system for the future connected society.展开更多
The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arr...The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arrays,beamforming can be adopted to improve the 5G capacity by employing spatial domain resources.In a frequency division duplexing(FDD)based 5G mmWave MIMO system,beamforming operation requires timely downlink channel state information(CSI)feedback.However,the rapid channel variations caused by short wavelength of mmWave band,and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead.In this paper,by exploiting the higher angular stability of such channels,we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits.To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming.Besides,location related feedback,which is not affected by the number of antennas,is adopted to reduce overhead.The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements,while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSIbased beamforming algorithm.展开更多
The fifth-generation(5G)wireless communication networks are expected to play an essential role in the transformation of vertical industries.Among many exciting applications to be enabled by 5G,logistics tasks in indus...The fifth-generation(5G)wireless communication networks are expected to play an essential role in the transformation of vertical industries.Among many exciting applications to be enabled by 5G,logistics tasks in industry parks can be performed more efficiently via vehicle-to-everything(V2X)communications.In this paper,a multi-layer collaboration framework enabled by V2X is proposed for logistics management in industrial parks.The proposed framework includes three layers:a perception and execution layer,a logistics layer,and a configuration layer.In addition to the collaboration among these three layers,this study addresses the collaboration among devices,edge servers,and cloud services.For effective logistics in industrial parks,task collaboration is achieved through four functions:environmental perception and map construction,task allocation,path planning,and vehicle movement.To dynamically coordinate these functions,device–edge–cloud collaboration,which is supported by 5G slices and V2X communication technology,is applied.Then,the analytical target cascading method is adopted to configure and evaluate the collaboration schemes of industrial parks.Finally,a logistics analytical case study in industrial parks is employed to demonstrate the feasibility of the proposed collaboration framework.展开更多
The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary characteristics.In this article,we focus on the most difficult HDC case,where the channel coherence time is ...The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary characteristics.In this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol period.To this end,we propose a symbol detector based on a long short-term memory(LSTM)neural network.Taking the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better performance.In addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network parameters.Finally,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube experiments.The results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.展开更多
Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount ...Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount of data generated by IoT devices remains a challenge to the building management systems(BMSs)in terms of intensity and complexity.Different from cloud computing and edge computing,we propose a computation sharing architecture in smart buildings to incentivize idle computing devices(ICDs,sellers)to offload computational tasks for the BMS(buyer).In this paper,we design a hierarchical game model,consisting of a Stackelberg game and a Cournot game,to achieve a dynamic increase in computational capacity for the BMS.To guarantee the utility of BMS and ICDs,the Stackelberg game model is built to analyze the interactions between BMS and ICDs.Then,the Cournot game model is presented to formulate the internal competition among multiple ICDs.Under the premise of the subgame perfect Nash equilibrium,the BMS can quote the optimal pricing strategy,and the ICDs can share the corresponding optimal amount of computing resources.Finally,the simulation results show that the BMS’s computational capacity is enhanced on-demand,and each participant in the game obtains maximal utility.展开更多
The economic impact of the geographical rotation of local officials is important in China's official management system.This study used a zero-inflated Poisson regression model and found that the geographical rotat...The economic impact of the geographical rotation of local officials is important in China's official management system.This study used a zero-inflated Poisson regression model and found that the geographical rotation of local officials significantly increased cross-city mergers and acquisitions(M&As)of enterprises.The impact of local officials'geographical rotation on M&As was more pronounced under certain conditions.These conditions included:(i)when officials were transferred from cities with a higher development level to cities with a lower development level;(ii)when the outflow cities were municipalities directly governed by the central government,provincial capitals,or separately listed cities;(iii)when the transfers of officials occurred within the same province;(iv)when the transfers took place before 2012;and(v)when the transfers happened in the years following significant central government conferences,which provided strong political incentives for M&As.展开更多
Unmanned Aerial Vehicles(UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generat...Unmanned Aerial Vehicles(UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generation(6G) networks due to their low cost and flexible deployment. 6G is supposed to be an all-coverage network to provide ubiquitous connections for space, air, ground and underwater. UAVs are able to provide air-borne wireless coverage flexibly,serving as aerial base stations for ground users, as relays to connect isolated nodes, or as mobile users in cellular networks. However, the onboard energy of small UAVs is extremely limited. Thus,UAVs can be only deployed to establish wireless links temporarily. Prolonging the lifetime and developing green UAV communication with low power consumption becomes a critical challenge.In this article, a comprehensive survey on green UAV communications for 6G is carried out. Specifically, the typical UAVs and their energy consumption models are introduced. Then, the typical trends of green UAV communications are provided. In addition, the typical applications of UAVs and their green designs are discussed. Finally, several promising techniques and open research issues are also pointed out.展开更多
The distributed optical fiber surface plasmon resonance(SPR)sensors have attracted wide attention in biosensing and chemical sensing applications.However,due to the limitation of their sensing structure,it is difficul...The distributed optical fiber surface plasmon resonance(SPR)sensors have attracted wide attention in biosensing and chemical sensing applications.However,due to the limitation of their sensing structure,it is difficult to adjust their res-onant wavelength and sensitivity.Here,novel and flexible cascaded helical-core fiber[HCF)SPR sensors are proposed theoretically and experimentally for distributed sensing applications.It is shown that the resonant wavelength and sensitivity of the sensors can be conveniently controlled by adjusting the twist pitch of the helical core.A high sensitivity of 11,180 nm/RIU for refractive-index measurement ranging from 1.355 to 1.365 is realized experimentally when the twist pitch of the helical core is 1.5 mm.It is worth noting that the sensitivity can be further improved by reducing the twist pitch.For example,the sensitivity of the sensor with a twist pitch of 1.4 mm can theoretically exceed 20,000 nm/RIU.This work opens up a new way to implement multi-parameter or distributed measurement,especially to establish sensing networks integrated in a single-core fiber or a multi-core fiber.展开更多
With a given communication protocol,performance optimization of a multiple-input multipleoutput(MIMO)wireless system mainly lies on the design of the radio frequency(RF)front end.Currently,the optimization is mainly a...With a given communication protocol,performance optimization of a multiple-input multipleoutput(MIMO)wireless system mainly lies on the design of the radio frequency(RF)front end.Currently,the optimization is mainly achieved based on experiences,such as promoting the multiple antenna gains and reducing their correlations.This experience-based method works to a certain extent,but is inefficient since the final performance impact by each sub-system is not quantified.The challenge lies on how to find the most limiting factor that restricts the overall communication throughput.This paper presents an analytical model for throughput calculations of 2×2 MIMO wireless system,which is built on a first step of maximum rate calculated under the chosen protocol and channel,followed by a second step of throughput baseline measurement,and continued with the third step of throughput calculations of the overall system according to the actual settings of subsystems.The model can provide a detailed diagnostic report of each RF factor,which will directly point out the imperfections and make the troubleshooting and debugging much more effective.Besides,throughput is analyzed in a mathematical approach that allows the performance more predictable during the design phase.展开更多
Network slicing is a key technology to support the concurrent provisioning of heterogeneous Quality of Service(QoS)in the 5th Generation(5G)-beyond and the 6th Generation(6G)networks.However,effective slicing of Radio...Network slicing is a key technology to support the concurrent provisioning of heterogeneous Quality of Service(QoS)in the 5th Generation(5G)-beyond and the 6th Generation(6G)networks.However,effective slicing of Radio Access Network(RAN)is very challenging due to the diverse QoS requirements and dynamic conditions in the 6G networks.In this paper,we propose a self-sustained RAN slicing framework,which integrates the self-management of network resources with multiple granularities,the self-optimization of slicing control performance,and self-learning together to achieve an adaptive control strategy under unforeseen network conditions.The proposed RAN slicing framework is hierarchically structured,which decomposes the RAN slicing control into three levels,i.e.,network-level slicing,next generation NodeB(gNodeB)-level slicing,and packet scheduling level slicing.At the network level,network resources are assigned to each gNodeB at a large timescale with coarse resource granularity.At the gNodeB-level,each gNodeB adjusts the configuration of each slice in the cell at the large timescale.At the packet scheduling level,each gNodeB allocates radio resource allocation among users in each network slice at a small timescale.Furthermore,we utilize the transfer learning approach to enable the transition from a model-based control to an autonomic and self-learning RAN slicing control.With the proposed RAN slicing framework,the QoS performance of emerging services is expected to be dramatically enhanced.展开更多
文摘Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access(NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying(CNAR) system for 5G is proposed by enabling the collaboration of source-relay(S-R) and relay-destination(R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR(S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.
文摘IEEE 802.11ax,which is an emerging WLAN standard,aims at providing highly efficient communication in ultra-dense wireless networks.However,due to a large number of stations(STAs)in the ultra-dense device deployment scenarios,the potentially high packet collision rate significantly decreases the communication efficiency of WLAN.In this paper,we propose an adaptive STA grouping scheme to overcome this dense network challenge in IEEE 802.11ax by using Buffer State Report(BSR)based Two-stage Mechanism(BTM).In order to achieve the optimal efficiency of BSR delivery,we analyze the functional relationship between STA number in group and Resource Unit(RU)efficiency.Based on this analysis results,an adaptive STA grouping algorithm with variable group size is proposed to achieve efficient grouping in BTM.The numerical results demonstrate that the proposed adaptive BTM grouping algorithm significantly improves the BSR delivery efficiency and the throughput of overall system and each STA in the ultra-dense wireless network.
基金support by National High Technology Research and Development Program of China (No. 2011AA050504)the analysis supports from Instrumental Analysis Center of SJTU
文摘A vertical carbon nanotube field-effect transistor(CNTFET) based on silicon(Si) substrate has been proposed and simulated using a semi-classical theory. A single-walled carbon nanotube(SWNT) and an n-type Si nanowire in series construct the channel of the transistor. The CNTFET presents ambipolar characteristics at positive drain voltage(Vd) and n-type characteristics at negative Vd. The current is significantly influenced by the doping level of n-Si and the SWNT band gap. The n-branch current of the ambipolar characteristics increases with increasing doping level of the n-Si while the p-branch current decreases. The SWNT band gap has the same influence on the p-branch current at a positive Vd and n-type characteristics at negative Vd. The lower the SWNT band gap, the higher the current. However, it has no impact on the n-branch current in the ambipolar characteristics. Thick oxide is found to significantly degrade the current and the subthreshold slope of the CNTFETs.
基金the financial support from Canada Innovation Fund-Leaders Opportunity Fundthe Natural Sciences and Engineering Research Council of Canada(NSERC).
文摘Very few materials show large magnetoresistance(MR)under a low magnetic field at room temperature,which causes the barrier to the development of magnetic field sensors for detecting low-level electromagnetic radiation in real-time.Here,a hybrid reduced graphene oxide(rGO)-based magnetic field sensor is produced by in situ deposition of FeCo nanoparticles(NPs)on reduced graphene oxide(rGO).Special quantum magnetoresistance(MR)of the hybrid rGO is observed,which unveils that Abrikosov's quantum model for layered materials can occur in hybrid rGO;meanwhile,the MR value can be tunable by adjusting the particle density of FeCo NPs on rGO nanosheets.Very high MR value up to 21.02±5.74%at 10 kOe at room temperature is achieved,and the average increasing rate of resistance per kOe is up to 0.9282ΩkOe^-1.In this paper,we demonstrate that the hybrid rGO-based magnetic field sensor can be embedded in a wireless system for real-time detection of low-level electromagnetic radiation caused by a working mobile phone.We believe that the two-dimensional nanomaterials with controllable MR can be integrated with a wireless system for the future connected society.
文摘The integration of millimeter-wave(mmWave)communications and massive multiple input multiple output(MIMO)techniques is a promising solution to dramatically increase the 5G network throughput.By using large antenna arrays,beamforming can be adopted to improve the 5G capacity by employing spatial domain resources.In a frequency division duplexing(FDD)based 5G mmWave MIMO system,beamforming operation requires timely downlink channel state information(CSI)feedback.However,the rapid channel variations caused by short wavelength of mmWave band,and the high-level feedback information required due to the large number of antennas in massive MIMO system lead to the significantly increased beamforming overhead.In this paper,by exploiting the higher angular stability of such channels,we propose an angle-based beamforming scheme to reduce the feedback frequency and the number of feedback bits.To facilitate this approach users are initially selected to reduce the intra-zone interference before beamforming.Besides,location related feedback,which is not affected by the number of antennas,is adopted to reduce overhead.The simulation results show that two proposed user selection algorithms can adapt to scenarios with diverse requirements,while the feedback overhead of proposed angle-based beamforming algorithm is sharply reduce compared with that of CSIbased beamforming algorithm.
基金supported by the China National Key Research and Development Program(2018YFE0197700).
文摘The fifth-generation(5G)wireless communication networks are expected to play an essential role in the transformation of vertical industries.Among many exciting applications to be enabled by 5G,logistics tasks in industry parks can be performed more efficiently via vehicle-to-everything(V2X)communications.In this paper,a multi-layer collaboration framework enabled by V2X is proposed for logistics management in industrial parks.The proposed framework includes three layers:a perception and execution layer,a logistics layer,and a configuration layer.In addition to the collaboration among these three layers,this study addresses the collaboration among devices,edge servers,and cloud services.For effective logistics in industrial parks,task collaboration is achieved through four functions:environmental perception and map construction,task allocation,path planning,and vehicle movement.To dynamically coordinate these functions,device–edge–cloud collaboration,which is supported by 5G slices and V2X communication technology,is applied.Then,the analytical target cascading method is adopted to configure and evaluate the collaboration schemes of industrial parks.Finally,a logistics analytical case study in industrial parks is employed to demonstrate the feasibility of the proposed collaboration framework.
基金supported in part by the National Key R&D Program of China under Grant 2020YFA0711301in part by the National Natural Science Foundation of China(No.61941104,62101292,61922049)。
文摘The highly dynamic channel(HDC)in an extremely dynamic environment mainly has fast timevarying nonstationary characteristics.In this article,we focus on the most difficult HDC case,where the channel coherence time is less than the symbol period.To this end,we propose a symbol detector based on a long short-term memory(LSTM)neural network.Taking the sampling sequence of each received symbol as the LSTM unit's input data has the advantage of making full use of received information to obtain better performance.In addition,using the basic expansion model(BEM)as the preprocessing unit significantly reduces the number of neural network parameters.Finally,the simulation part uses the highly dynamic plasma sheath channel(HDPSC)data measured from shock tube experiments.The results show that the proposed BEM-LSTM-based detector has better performance and does not require channel estimation or channel model information.
基金in part by the Natural Science Foundation of China under Grant 61871446,61801238the Postgraduate Research&Practice Innovation Program of Jiangsu Province under Grant KYCX18_0887the Natural Science Foundation of Jiangsu Province under Grant BK20170758.
文摘Recently,initiatives to integrate Internet of Things(IoT)technologies into smart buildings have attracted extensive attention for improving the performance of buildings and the comfort of occupants.However,the amount of data generated by IoT devices remains a challenge to the building management systems(BMSs)in terms of intensity and complexity.Different from cloud computing and edge computing,we propose a computation sharing architecture in smart buildings to incentivize idle computing devices(ICDs,sellers)to offload computational tasks for the BMS(buyer).In this paper,we design a hierarchical game model,consisting of a Stackelberg game and a Cournot game,to achieve a dynamic increase in computational capacity for the BMS.To guarantee the utility of BMS and ICDs,the Stackelberg game model is built to analyze the interactions between BMS and ICDs.Then,the Cournot game model is presented to formulate the internal competition among multiple ICDs.Under the premise of the subgame perfect Nash equilibrium,the BMS can quote the optimal pricing strategy,and the ICDs can share the corresponding optimal amount of computing resources.Finally,the simulation results show that the BMS’s computational capacity is enhanced on-demand,and each participant in the game obtains maximal utility.
基金supported financially by the National Natural Science Foundation of China (Nos.72073047 and 72273052)the Natural Science Foundation of Guangdong Province (No.2021A1515011983)the Guangzhou Philosophy and Social Science Planning Project (No.2021GZYB01).
文摘The economic impact of the geographical rotation of local officials is important in China's official management system.This study used a zero-inflated Poisson regression model and found that the geographical rotation of local officials significantly increased cross-city mergers and acquisitions(M&As)of enterprises.The impact of local officials'geographical rotation on M&As was more pronounced under certain conditions.These conditions included:(i)when officials were transferred from cities with a higher development level to cities with a lower development level;(ii)when the outflow cities were municipalities directly governed by the central government,provincial capitals,or separately listed cities;(iii)when the transfers of officials occurred within the same province;(iv)when the transfers took place before 2012;and(v)when the transfers happened in the years following significant central government conferences,which provided strong political incentives for M&As.
基金supported by the National Key R&D Program of China(No.2020YFB1807002)the China Postdoctoral Science Foundation(No.2020M680949)+1 种基金the Open Research fund of State Key Laboratory of Integrated Services Networks,China(No.ISN22-22)the National Natural Science Foundation of China(Nos.61871065 and U1836201)。
文摘Unmanned Aerial Vehicles(UAVs) have received a wide range of attention for military and commercial applications. Enhanced with communication capability, UAVs are considered to play important roles in the Sixth Generation(6G) networks due to their low cost and flexible deployment. 6G is supposed to be an all-coverage network to provide ubiquitous connections for space, air, ground and underwater. UAVs are able to provide air-borne wireless coverage flexibly,serving as aerial base stations for ground users, as relays to connect isolated nodes, or as mobile users in cellular networks. However, the onboard energy of small UAVs is extremely limited. Thus,UAVs can be only deployed to establish wireless links temporarily. Prolonging the lifetime and developing green UAV communication with low power consumption becomes a critical challenge.In this article, a comprehensive survey on green UAV communications for 6G is carried out. Specifically, the typical UAVs and their energy consumption models are introduced. Then, the typical trends of green UAV communications are provided. In addition, the typical applications of UAVs and their green designs are discussed. Finally, several promising techniques and open research issues are also pointed out.
基金supported by the National Key R&D Program of China (No. 2017YFB0405501)the National Natural Science Foundation of China (Nos. 61705050, 61675052, 61965005, 61975038, and 61827819)the Guangxi Project (Nos. 2018AD19081 and 2018AA20001)
文摘The distributed optical fiber surface plasmon resonance(SPR)sensors have attracted wide attention in biosensing and chemical sensing applications.However,due to the limitation of their sensing structure,it is difficult to adjust their res-onant wavelength and sensitivity.Here,novel and flexible cascaded helical-core fiber[HCF)SPR sensors are proposed theoretically and experimentally for distributed sensing applications.It is shown that the resonant wavelength and sensitivity of the sensors can be conveniently controlled by adjusting the twist pitch of the helical core.A high sensitivity of 11,180 nm/RIU for refractive-index measurement ranging from 1.355 to 1.365 is realized experimentally when the twist pitch of the helical core is 1.5 mm.It is worth noting that the sensitivity can be further improved by reducing the twist pitch.For example,the sensitivity of the sensor with a twist pitch of 1.4 mm can theoretically exceed 20,000 nm/RIU.This work opens up a new way to implement multi-parameter or distributed measurement,especially to establish sensing networks integrated in a single-core fiber or a multi-core fiber.
基金This work was supported in part by Chinese Ministry of Education—China Mobile Research Foundation under Grant MCM 20150101in part by National Natural Science Foundation of China under Grant 61671203.
文摘With a given communication protocol,performance optimization of a multiple-input multipleoutput(MIMO)wireless system mainly lies on the design of the radio frequency(RF)front end.Currently,the optimization is mainly achieved based on experiences,such as promoting the multiple antenna gains and reducing their correlations.This experience-based method works to a certain extent,but is inefficient since the final performance impact by each sub-system is not quantified.The challenge lies on how to find the most limiting factor that restricts the overall communication throughput.This paper presents an analytical model for throughput calculations of 2×2 MIMO wireless system,which is built on a first step of maximum rate calculated under the chosen protocol and channel,followed by a second step of throughput baseline measurement,and continued with the third step of throughput calculations of the overall system according to the actual settings of subsystems.The model can provide a detailed diagnostic report of each RF factor,which will directly point out the imperfections and make the troubleshooting and debugging much more effective.Besides,throughput is analyzed in a mathematical approach that allows the performance more predictable during the design phase.
文摘Network slicing is a key technology to support the concurrent provisioning of heterogeneous Quality of Service(QoS)in the 5th Generation(5G)-beyond and the 6th Generation(6G)networks.However,effective slicing of Radio Access Network(RAN)is very challenging due to the diverse QoS requirements and dynamic conditions in the 6G networks.In this paper,we propose a self-sustained RAN slicing framework,which integrates the self-management of network resources with multiple granularities,the self-optimization of slicing control performance,and self-learning together to achieve an adaptive control strategy under unforeseen network conditions.The proposed RAN slicing framework is hierarchically structured,which decomposes the RAN slicing control into three levels,i.e.,network-level slicing,next generation NodeB(gNodeB)-level slicing,and packet scheduling level slicing.At the network level,network resources are assigned to each gNodeB at a large timescale with coarse resource granularity.At the gNodeB-level,each gNodeB adjusts the configuration of each slice in the cell at the large timescale.At the packet scheduling level,each gNodeB allocates radio resource allocation among users in each network slice at a small timescale.Furthermore,we utilize the transfer learning approach to enable the transition from a model-based control to an autonomic and self-learning RAN slicing control.With the proposed RAN slicing framework,the QoS performance of emerging services is expected to be dramatically enhanced.
