This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state informat...This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),respectively.The outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based grouping.It is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently low.Besides,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell interference.Moreover,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves oppositely.Afterwards,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission rates.In the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.展开更多
The mammals can not only entrain to the natural 24-h light–dark cycle, but also to the artificial cycle with non 24-h period through the main clock named suprachiasmatic nucleus in the brain. The range of the periods...The mammals can not only entrain to the natural 24-h light–dark cycle, but also to the artificial cycle with non 24-h period through the main clock named suprachiasmatic nucleus in the brain. The range of the periods of the artificial cycles which the suprachiasmatic nucleus(SCN) can entrain, is called entrainment range reflecting the flexibility of the SCN. The SCN can be divided into two groups of neurons functionally, based on the different sensitivities to the light information. In the present study, we examined whether the entrainment range is affected by this difference in the sensitivity by a Poincaré model. We found that the relationship of the entrainment range to the difference depends on the coupling between two groups. When the coupling strength is much smaller than the light intensity, the relationship is parabolic-like, and the maximum of the entrainment range is obtained with no difference of the sensitivity. When the coupling strength is much larger than the light intensity, the relationship is monotonically changed, and the maximum of the entrainment range is obtained when the difference is the largest. Our finding may provide an explanation for the exitance of the difference in the sensitivity to light-information as well as shed light on how to increase the flexibility of the SCN represented by widening the entrainment range.展开更多
This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a tri...This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a trigger time. For this purpose, we propose the communication-censored distributed learning algorithm for SCN, namely ADMMM-SCN-ET, by introducing the event-triggered communication mechanism to the alternating direction method of multipliers (ADMM). To avoid unnecessary information transmissions, each learning agent is equipped with a trigger function. Only if the event-trigger error exceeds a specified threshold and meets the trigger condition, the agent will transmit the variable information to its neighbors and update its state in time. The simulation results show that the proposed algorithm can effectively reduce the communication cost for training decentralized SCNs and save communication resources.展开更多
Supply chain management(SCM)and its associated activities continue to evolve as new communication technologies and cooperative efforts emerge to facilitate system-wide process integration;the context within which supp...Supply chain management(SCM)and its associated activities continue to evolve as new communication technologies and cooperative efforts emerge to facilitate system-wide process integration;the context within which supply chains(SCs)operate,the technologies,and performance enhancement mechanisms have all changed.Thus,linear-based SCs are increasingly being challenged as firms look towards a more networked approach to maximize performance amid growing market dynamics.This paper,however,recognizing inherent similarities between social structure of Social Internet of Things(SIoT)principles and what we term supply community networks(SCN)from literature,seeks to cross-pollinate the two in a way capable of dealing with these market dynamics.Our contribution is,therefore,a new‘setting’of social relationships between supply community agents(SCA)within SCN mirroring interactions played out in the physical world;SCAs autonomously sense each other,exchange information and interact within SCN mimicking the behavior of humans.Also,it identifies the bounds of flow,i.e.all possible dimensions within a SCN which need to be understood to support relationship management.Therefore,communications are improved,sharpening SCAs synchronization in a way responsive to customer needs.展开更多
为了提高卫星通信网评估系统的适应能力和可扩展性,以满足因卫星通信网快速建设而产生的评估需求,利用本体知识表示的共享和重用特性,在卫星通信网评估本体(satellite communication network evaluation ontology,SCNEO)的基础上,提出...为了提高卫星通信网评估系统的适应能力和可扩展性,以满足因卫星通信网快速建设而产生的评估需求,利用本体知识表示的共享和重用特性,在卫星通信网评估本体(satellite communication network evaluation ontology,SCNEO)的基础上,提出了一种卫星通信网评估自适应技术,实现了任意对象定义和指标体系平面化。采用该技术,在应用和具体数据之间建立了清晰的功能界面,大大提高了卫星通信网评估系统的自适应能力,可有效提高系统开发效率。展开更多
基金supported in part by the National Key Research and Development Program of China under Grant 2017YFE0120600in part by National Natural Science Foundation of China under Grants 61801192,62171200,and 61801246+7 种基金in part by Guangdong Basic and Applied Basic Research Foundation under Grant 2019A1515012136in part by Natural Science Foundation of Anhui Province under Grant 1808085MF164in part by the Science and Technology Planning Project of Guangdong Province under Grants 2018B010114002 and 2019B010137006in part by the Science and Technology Development Fund,Macao SAR(File no.0036/2019/A1 and File no.SKL-IOTSC2021-2023)in part by the Hong Kong Presidents Advisory Committee on Research and Development(PACRD)under Project No.2020/1.6in part by Qinglan Project of University of Jiangsu Provincein part by the Research Committee of University of Macao under Grant MYRG2018-00156-FSTin part by 2018 Guangzhou Leading Innovation Team Program(China)under Grant 201909010006。
文摘This paper focuses on boosting the performance of small cell networks(SCNs)by integrating multiple-input multiple-output(MIMO)and nonorthogonal multiple access(NOMA)in consideration of imperfect channel-state information(CSI).The estimation error and the spatial randomness of base stations(BSs)are characterized by using Kronecker model and Poisson point process(PPP),respectively.The outage probabilities of MIMO-NOMA enhanced SCNs are first derived in closed-form by taking into account two grouping policies,including random grouping and distance-based grouping.It is revealed that the average outage probabilities are irrelevant to the intensity of BSs in the interference-limited regime,while the outage performance deteriorates if the intensity is sufficiently low.Besides,as the channel uncertainty lessens,the asymptotic analyses manifest that the target rates must be restricted up to a bound to achieve an arbitrarily low outage probability in the absence of the inter-cell interference.Moreover,highly correlated estimation error ameliorates the outage performance under a low quality of CSI,otherwise it behaves oppositely.Afterwards,the goodput is maximized by choosing appropriate precoding matrix,receiver filters and transmission rates.In the end,the numerical results verify our analysis and corroborate the superiority of our proposed algorithm.
基金National Natural Science Foundation of China(Grant Nos.11875042 and 11505114)the Innovation Foundation of Shanghai Aerospace Science and Technology,China(Grant No.SAST2018-22)the Course of Scientific Research Project of Shanghai University for Science and Technology(Grant No.13002100).
文摘The mammals can not only entrain to the natural 24-h light–dark cycle, but also to the artificial cycle with non 24-h period through the main clock named suprachiasmatic nucleus in the brain. The range of the periods of the artificial cycles which the suprachiasmatic nucleus(SCN) can entrain, is called entrainment range reflecting the flexibility of the SCN. The SCN can be divided into two groups of neurons functionally, based on the different sensitivities to the light information. In the present study, we examined whether the entrainment range is affected by this difference in the sensitivity by a Poincaré model. We found that the relationship of the entrainment range to the difference depends on the coupling between two groups. When the coupling strength is much smaller than the light intensity, the relationship is parabolic-like, and the maximum of the entrainment range is obtained with no difference of the sensitivity. When the coupling strength is much larger than the light intensity, the relationship is monotonically changed, and the maximum of the entrainment range is obtained when the difference is the largest. Our finding may provide an explanation for the exitance of the difference in the sensitivity to light-information as well as shed light on how to increase the flexibility of the SCN represented by widening the entrainment range.
文摘This paper aims to reduce the communication cost of the distributed learning algorithm for stochastic configuration networks (SCNs), in which information exchange between the learning agents is conducted only at a trigger time. For this purpose, we propose the communication-censored distributed learning algorithm for SCN, namely ADMMM-SCN-ET, by introducing the event-triggered communication mechanism to the alternating direction method of multipliers (ADMM). To avoid unnecessary information transmissions, each learning agent is equipped with a trigger function. Only if the event-trigger error exceeds a specified threshold and meets the trigger condition, the agent will transmit the variable information to its neighbors and update its state in time. The simulation results show that the proposed algorithm can effectively reduce the communication cost for training decentralized SCNs and save communication resources.
文摘Supply chain management(SCM)and its associated activities continue to evolve as new communication technologies and cooperative efforts emerge to facilitate system-wide process integration;the context within which supply chains(SCs)operate,the technologies,and performance enhancement mechanisms have all changed.Thus,linear-based SCs are increasingly being challenged as firms look towards a more networked approach to maximize performance amid growing market dynamics.This paper,however,recognizing inherent similarities between social structure of Social Internet of Things(SIoT)principles and what we term supply community networks(SCN)from literature,seeks to cross-pollinate the two in a way capable of dealing with these market dynamics.Our contribution is,therefore,a new‘setting’of social relationships between supply community agents(SCA)within SCN mirroring interactions played out in the physical world;SCAs autonomously sense each other,exchange information and interact within SCN mimicking the behavior of humans.Also,it identifies the bounds of flow,i.e.all possible dimensions within a SCN which need to be understood to support relationship management.Therefore,communications are improved,sharpening SCAs synchronization in a way responsive to customer needs.
文摘为了提高卫星通信网评估系统的适应能力和可扩展性,以满足因卫星通信网快速建设而产生的评估需求,利用本体知识表示的共享和重用特性,在卫星通信网评估本体(satellite communication network evaluation ontology,SCNEO)的基础上,提出了一种卫星通信网评估自适应技术,实现了任意对象定义和指标体系平面化。采用该技术,在应用和具体数据之间建立了清晰的功能界面,大大提高了卫星通信网评估系统的自适应能力,可有效提高系统开发效率。
