In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best conn...In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.展开更多
This paper studies the problem of effective resource allocation for multi-radio access technologies （Multi-RAT） nodes in heterogeneous cognitive wireless networks （HCWNs）. End-to-end utility, which is defined as t...This paper studies the problem of effective resource allocation for multi-radio access technologies （Multi-RAT） nodes in heterogeneous cognitive wireless networks （HCWNs）. End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.展开更多
目的:研究神经干细胞(NSCs)的分离、培养及鉴定方法。方法:以孕12.5 d SD胚胎鼠端脑为组织来源,应用无血清悬浮培养技术培养、扩增NSCs;NSCs传代2次后,应用Nestin免疫荧光检测NSCs的干细胞特性,Brd U标记法检测细胞增殖能力;诱导贴壁分...目的:研究神经干细胞(NSCs)的分离、培养及鉴定方法。方法:以孕12.5 d SD胚胎鼠端脑为组织来源,应用无血清悬浮培养技术培养、扩增NSCs;NSCs传代2次后,应用Nestin免疫荧光检测NSCs的干细胞特性,Brd U标记法检测细胞增殖能力;诱导贴壁分化后,对分化细胞进行NSE、GFAP免疫荧光鉴定;扫描电镜观察神经球及单个细胞表型。结果:培养出大量悬浮生长的NSCs球,Nestin及Brd U表达阳性;神经球诱导分化后表达NSE、GFAP,表明NSCs可分化为神经元和星形胶质细胞;HE染色可见NSCs细胞核巨大,胞质较少;扫描电镜可观察到单个NSC表面较光滑,且神经球表面的NSCs连接较疏散。结论:应用无血清培养技术体外培养扩增出的胚胎神经干细胞具有自我更新和多向分化能力,经诱导后可分化为神经元和星形胶质细胞。展开更多
基金supported by the National Natural Science Fund of China(Grant NO.61771065,Grant NO.61571054 and Grant NO.61631005)Beijing Nova Program(NO.Z151100000315077)
文摘In the upcoming 5 G heterogeneous networks, leveraging multiple radio access technologies(RATs) shows to be a crucial issue in achieving RAT multiplexing gain to meet the explosive traffic demand. For always best connection(ABC), users tend to activate parallel transmission across all available RATs. However from a system-wide perspective, this might not be optimal given the context of network load, interference and diverse service requirements. To intelligently determine how to use these multi-RAT access resources concurrently, this paper proposes a joint multi-RAT user association and resource allocation strategy with triple decision and integrated context awareness of users and networks. A dynamic game based ant colony algorithm(GACA) is designed to simultaneously maximize the system utility and the fairness of resource allocation. Simulation results show that it's more reasonable to make multi-RAT association decision from a system-wide viewpoint than from an individual one. Compared to max-SNR based and ABC based strategies, the proposed method alleviates network congestion and optimizes resource allocation. It obtains 39%~70% performance improvement.
基金supported by National Basic Research Program of China(2009CB320401)the National Key Scientific and Technological Project of China(2008ZX03003-005,2008ZX03003)+1 种基金the Fundamental Research Funds for the Central Universities BUPT2009RC0111Research Funds of Doctoral Program of Higher Education of China(20090005110003)
文摘This paper studies the problem of effective resource allocation for multi-radio access technologies （Multi-RAT） nodes in heterogeneous cognitive wireless networks （HCWNs）. End-to-end utility, which is defined as the delay of end-to-end communication, is taken into account in this paper. In the scenario of HCWNs, it is assumed that the cognitive radio nodes have the ability of Multi-RAT and can communicate with each other through different paths simultaneously by splitting the arrival packets. In this paper, the problem is formulated as the optimization of split ratio and power allocation of the source cognitive radio node to minimize the delay of end-to-end communication, and a low complexity step-by-step iterative algorithm is proposed. Numerical results show good performance of the proposed algorithm over two other conventional algorithms.
文摘目的:研究神经干细胞(NSCs)的分离、培养及鉴定方法。方法:以孕12.5 d SD胚胎鼠端脑为组织来源,应用无血清悬浮培养技术培养、扩增NSCs;NSCs传代2次后,应用Nestin免疫荧光检测NSCs的干细胞特性,Brd U标记法检测细胞增殖能力;诱导贴壁分化后,对分化细胞进行NSE、GFAP免疫荧光鉴定;扫描电镜观察神经球及单个细胞表型。结果:培养出大量悬浮生长的NSCs球,Nestin及Brd U表达阳性;神经球诱导分化后表达NSE、GFAP,表明NSCs可分化为神经元和星形胶质细胞;HE染色可见NSCs细胞核巨大,胞质较少;扫描电镜可观察到单个NSC表面较光滑,且神经球表面的NSCs连接较疏散。结论:应用无血清培养技术体外培养扩增出的胚胎神经干细胞具有自我更新和多向分化能力,经诱导后可分化为神经元和星形胶质细胞。
