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Multi-Radio Cooperation Technology and Heterogeneous Network Convergence 被引量:1
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作者 Huang Chuan, Zheng Baoyu (Institute of Signal Processing and Transmission, Nanjing University of Posts and Telecommunications, Nanjing 210003, China) 《ZTE Communications》 2008年第3期29-33,共5页
The heterogeneous network convergence is the trend of future network development. However, many bottlenecks exist in the converged system such as high time delay, high energy consumption, and low data rate. Multi-Radi... The heterogeneous network convergence is the trend of future network development. However, many bottlenecks exist in the converged system such as high time delay, high energy consumption, and low data rate. Multi-Radio Cooperation (MRC) technology is specially designed to overcome these bottlenecks and to satisfy the requirements of heterogeneous network convergence. MRC can improve network capacity, reduce the energy consumption of radio devices, and decrease handover latency between heterogeneous networks by the cooperation of multiple radios, and by efficient management and feasible allocation of multi-radio resources. MRC makes real seamless heterogeneous network convergence possible. 展开更多
关键词 RADIO RATE data Multi-Radio Cooperation Technology and heterogeneous Network convergence MRC WMN
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Study on QoS and Communications Capacity in Heterogeneous Network Convergence
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作者 Xia Weiwei,Shen Lianfeng(National Mobile Communications Research Laboratory,Southeast University,Nanjing 210096,China) 《ZTE Communications》 2008年第3期6-9,共4页
To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to b... To provide any subscriber from anywhere at anytime with services that have both secured Quality of Service(QoS) and simultaneous expansion of network coverage and communications capacity is a key problem that has to be considered and solved in heterogeneous network convergence.Key technologies for a secured QoS and communications capacity analysis under heterogeneous environment are important subjects for research.Key technologies for a secured QoS are mainly on radio resource management algorithms covering Call Admission Control(CAC) algorithm,vertical handover algorithm,heterogeneous resource allocation algorithm and network selection algorithm.The applications of a novel multi-hop in heterogeneous convergence system serve the purposes of network coverage expansion,transmission power reduction,system communication capacity and throughput increase. 展开更多
关键词 QOS Study on QoS and Communications Capacity in heterogeneous Network convergence WLAN IEEE
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Cognition Flow in Cognitive Radio Networks 被引量:2
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作者 许文俊 林家儒 +2 位作者 冯志勇 徐文波 张平 《China Communications》 SCIE CSCD 2013年第10期74-90,共17页
This paper introduces the research progress on the cognition flow in the National Basic Research Program of China(973 Program)under Grant No. 2009CB320400 "Research on Basic Theories and Key Technologies of Cogni... This paper introduces the research progress on the cognition flow in the National Basic Research Program of China(973 Program)under Grant No. 2009CB320400 "Research on Basic Theories and Key Technologies of Cognitive Radio Networks". We present the motivation behind the proposal of the concept of cognition flow, provide the definition, discuss the features, behaviours, representations, mathematical models, and the functions of cognition flow in Cognitive Radio Networks(CRNs). We also analyse how the cognition flow promotes the convergence of heterogeneous networks.Our group also constructed the test platform to verify the usefulness of cognition flow. The results that were simulated by computers and tested on the platform both confirm that cognition flow can realise efficient interaction of cognitive information among heterogeneous networks in CRNs, which contributes to the seamless convergence of heterogeneous networks,and significantly improves the spectrum efficiency and users' Quality of Experience(QoE). 展开更多
关键词 cognition flow CRN heterogeneous network convergence QOE
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