5G sets an ambitious goal of increasing the capacity per area of current 4G network by 1000 fold. Due to the high splitting gain of dense small cells, ultra dense network(UDN) is widely considered as a key component i...5G sets an ambitious goal of increasing the capacity per area of current 4G network by 1000 fold. Due to the high splitting gain of dense small cells, ultra dense network(UDN) is widely considered as a key component in achieving this goal. In this paper, we outline the main challenges that come with dense cell deployment, including interference, mobility, power consumption and backhaul. Technologies designed to tackle these challenges in long term evolution system(LTE) and their deficiencies in UDN context are also analyzed. To combat these challenges more efficiently, a series of technologies are introduced along with some of our initial research results. Moreover, the trends of user-centric and peer-to-peer design in UDN are also elaborated.展开更多
Multiple access scheme is one of the key techniques in wireless communication systems. Each generation of wireless communica-tion is featured by a new multiple access scheme from 1G to 4G. In this article we review se...Multiple access scheme is one of the key techniques in wireless communication systems. Each generation of wireless communica-tion is featured by a new multiple access scheme from 1G to 4G. In this article we review several non-orthogonal multiple access schemes for 5G. Their principles, advantages and disadvantages are discussed, and followed by a comprehensive comparison of these solutions from the perspective of user overload, receiver type, receiver complexity and so on. We also discuss the application challenges of non-orthogonal multiple access schemes in 5G.展开更多
Over the past two years,reconfigurable intelligent surface(RIS),as a promising emerging technology for Beyond 5 G(B5 G) and 6 G mobile communications systems,has attracted enormous interest from both academia and indu...Over the past two years,reconfigurable intelligent surface(RIS),as a promising emerging technology for Beyond 5 G(B5 G) and 6 G mobile communications systems,has attracted enormous interest from both academia and industry worldwide.In IMT-2030(6 G) Promotion Group of China,the RIS task force was created in June 2020.展开更多
The emerging fifth generation(5G)network has the potential to satisfy the rapidly growing traffic demand and promote the transformation of smartphone-centric networks into an Internet of Things(IoT)ecosystem.Due to th...The emerging fifth generation(5G)network has the potential to satisfy the rapidly growing traffic demand and promote the transformation of smartphone-centric networks into an Internet of Things(IoT)ecosystem.Due to the introduction of new communication technologies and the increased density of 5G cells,the complexity of operation and operational expenditure(OPEX)will become very challenging in 5G.Self-organizing network(SON)has been researched extensively since 2G,to cope with the similar challenge,however by predefined poli cies,rather than intelligent analysis.The requirement for better quality of experience and the complexity of 5G network demands call for an approach that is different from SON.In several recent studies,the combination of machine learning(ML)technology with SON has been investi gated.In this paper,we focus on the intelligent operation of wireless network through ML algo rithms.A comprehensive and flexible framework is proposed to achieve an intelligent operation system.Two use cases are also studied to use ML algorithms to automate the anomaly detection and fault diagnosis of key performance indicators(KPIs)in wireless networks.The effectiveness of the proposed ML algorithms is demonstrated by the real data experiments,thus encouraging the further research for intelligent wireless network operation.展开更多
文摘5G sets an ambitious goal of increasing the capacity per area of current 4G network by 1000 fold. Due to the high splitting gain of dense small cells, ultra dense network(UDN) is widely considered as a key component in achieving this goal. In this paper, we outline the main challenges that come with dense cell deployment, including interference, mobility, power consumption and backhaul. Technologies designed to tackle these challenges in long term evolution system(LTE) and their deficiencies in UDN context are also analyzed. To combat these challenges more efficiently, a series of technologies are introduced along with some of our initial research results. Moreover, the trends of user-centric and peer-to-peer design in UDN are also elaborated.
文摘Multiple access scheme is one of the key techniques in wireless communication systems. Each generation of wireless communica-tion is featured by a new multiple access scheme from 1G to 4G. In this article we review several non-orthogonal multiple access schemes for 5G. Their principles, advantages and disadvantages are discussed, and followed by a comprehensive comparison of these solutions from the perspective of user overload, receiver type, receiver complexity and so on. We also discuss the application challenges of non-orthogonal multiple access schemes in 5G.
文摘Over the past two years,reconfigurable intelligent surface(RIS),as a promising emerging technology for Beyond 5 G(B5 G) and 6 G mobile communications systems,has attracted enormous interest from both academia and industry worldwide.In IMT-2030(6 G) Promotion Group of China,the RIS task force was created in June 2020.
基金sponsored by Shanghai Sailing Program under Grant No.18YF1423300.
文摘The emerging fifth generation(5G)network has the potential to satisfy the rapidly growing traffic demand and promote the transformation of smartphone-centric networks into an Internet of Things(IoT)ecosystem.Due to the introduction of new communication technologies and the increased density of 5G cells,the complexity of operation and operational expenditure(OPEX)will become very challenging in 5G.Self-organizing network(SON)has been researched extensively since 2G,to cope with the similar challenge,however by predefined poli cies,rather than intelligent analysis.The requirement for better quality of experience and the complexity of 5G network demands call for an approach that is different from SON.In several recent studies,the combination of machine learning(ML)technology with SON has been investi gated.In this paper,we focus on the intelligent operation of wireless network through ML algo rithms.A comprehensive and flexible framework is proposed to achieve an intelligent operation system.Two use cases are also studied to use ML algorithms to automate the anomaly detection and fault diagnosis of key performance indicators(KPIs)in wireless networks.The effectiveness of the proposed ML algorithms is demonstrated by the real data experiments,thus encouraging the further research for intelligent wireless network operation.
