Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous ch...Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.展开更多
In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimatio...In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.展开更多
The cloud radio access network(C-RAN) has recently been proposed as an important component of the next generation wireless networks providing opportunities for improving both spectral and energy effi ciencies. The per...The cloud radio access network(C-RAN) has recently been proposed as an important component of the next generation wireless networks providing opportunities for improving both spectral and energy effi ciencies. The performance of this network structure is however constrained by severe inter-cell interference due to the limited capacity of fronthaul between the radio remote heads(RRH) and the base band unit(BBU) pool. To achieve performance improvement taking full advantage of centralized processing capabilities of C-RANs,a set of RRHs can jointly transmit data to the same UE for improved spectral effi ciency. In this paper,a user centralized joint coordinated transmission(UC-JCT) scheme is put forth to investigate the downlink performance of C-RANs. The most important benefit the proposed strategy is the ability to translate what would have been the most dominant interfering sources to usable signal leading to a signifi cantly improved performance. Stochastic geometry is utilized to model the randomness of RRH location and provides a reliable performance analysis. We derive an analytical expression for the closed integral form of the coverage probability of a typical UE. Simulation results confirm the accuracy of our analysis and demonstrate that significant performance gain can be achieved from the proposed coordination schemes.展开更多
Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless...Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless network.Nevertheless,to further enhance the capacity and coverage,more radio remote heads(RRHs)as well as high-fidelity and low-latency fronthaul links are required,which may lead to high implementation cost.To address this issue,we propose to exploit the intelligent reflecting surface(IRS)as an alternative way to enhance the C-RAN,which is a low-cost and energy-efficient option.Specifically,we consider the uplink transmission where multi-antenna users communicate with the baseband unit(BBU)pool through multi-antenna RRHs and multiple IRSs are deployed between the users and RRHs.RRHs can conduct either point-to-point(P2P)compression or Wyner-Ziv coding to compress the received signals,which are then forwarded to the BBU pool through fronthaul links.We investigate the joint design and optimization of user transmit beamformers,IRS passive beamformers,and fronthaul compression noise covariance matrices to maximize the uplink sum rate subject to fronthaul capacity constraints under P2P compression and Wyner-Ziv coding.By exploiting the Arimoto-Blahut algorithm and semi-definite relaxation(SDR),we propose a successive convex approximation approach to solve non-convex problems,and two iterative algorithms corresponding to P2P compression and Wyner-Ziv coding are provided.Numerical results verify the performance gain brought about by deploying IRS in C-RAN and the superiority of the proposed joint design.展开更多
The installation of small cells in a 5G network extends the maximum coverage and provides high availability.However,this approach increases the handover overhead in the Core Network(CN)due to frequent handoffs.The var...The installation of small cells in a 5G network extends the maximum coverage and provides high availability.However,this approach increases the handover overhead in the Core Network(CN)due to frequent handoffs.The variation of user density and movement inside a region of small cells also increases the handover overhead in CN.However,the present 5G system cannot reduce the handover overhead in CN under such circumstances because it relies on a traditionally rigid and complex hierarchical sequence for a handover procedure.Recently,Not Only Stack(NO Stack)architecture has been introduced for Radio Access Network(RAN)to reduce the signaling during handover.This paper proposes a system based on NO Stack architecture and solves the aforementioned problem by adding a dedicated local mobility controller to the edge cloud for each cluster.The dedicated cluster controller manages the user mobility locally inside a cluster and also maintains the forwarding data of a mobile user locally.To reduce the latency for X2-based handover requests,an edge cloud infrastructure has been also developed to provide high-computing for dedicated controllers at the edge of a cellular network.The proposed system is also compared with the traditional 3GPP architecture and other works in the context of overhead and delay caused by X2-based handover requests during user mobility.Simulated results show that the inclusion of a dedicated local controller for small clusters together with the implementation of NO Stack framework reduces the significant amount of overhead of X2-based handover requests at CN.展开更多
Cloud computing is the latest major evolution in computing technology. The convergence between cloud computing and tele- com networks could significantly reduce costs and bring new business opportunities for operators...Cloud computing is the latest major evolution in computing technology. The convergence between cloud computing and tele- com networks could significantly reduce costs and bring new business opportunities for operators. Currently, traditional teleeom operators are embarrassed by the fact that the increase in revenue cannot catch up with the quick growth of users and the expansion of networks. With the introduction of the cloud computing technology, operators can virtualize the network functions through low-cost COTS IT hardware All kinds of existing services can be cloudifled and thus obtain the benefits of statistical multiplexing among IT resources. With the Teleo Cloud architecture, operators can manage both IT infrastructures and network resources intelligently in order to adapt to the dynamic demands from the application and to establish open platforms for developing new services.展开更多
基金supported in part by the National High Technology Research and Development Program of China(Grant No.2014AA01A707)the Beijing Natural Science Foundation(Grant No.4131003)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP)(Grant No.20120005140002)the Key Program of Science and Technology Development Project of Beijing Municipal Education Commission of China (KZ201511232036)
文摘Relay in full-duplex(FD) mode can achieve higher spectrum efficiency than that in half-duplex mode,while it is crucial to suppress relay self-interference to ensure transmission quality which requires instantaneous channel state information(CSI). In this paper,the channel estimation issue in FD amplify-andforward relay networks is considered,where the training-based estimation technique is adopted. Firstly,the least square(LS) estimation is implemented to obtain composite channel coefficients of source-relay-destination(SRD) channel and relay loop-interference(LI) channel in order to assist destination in performing data detection. Secondly,both LS and maximum likelihood estimation methods are utilized to perform individual channel estimation aiming at supporting successive interference cancelation at destination. Finally,simulation results demonstrate the effectiveness of both composite and individual channel estimation,and the presented ML method can achieve lower MSEs than LS solution.
基金supported in part by the the National High Technology Research and Devel-opment Program of China(Grant No.2014AA01A701)National Natural Science Foundation of China(Grant No.61361166005)+2 种基金the State Major Science and Technology Special Projects(Grant No.2016ZX03001020006)the National Program for Support of Top-notch Young Pro-fessionalsthe Science and Technology Development Project of Beijing Municipal Education Commission of China(Grant No.KZ201511232036)
文摘In this paper, a quasi-Newton method fbr semi-blind estimation is derived for channel estimation in uplink cloud radio access networks （C-RANs）. Different from traditional pilot-aided estimation, semiblind estimation utilizes the unknown data symbols in addition to the known pilot symbols to estimate the channel. An initial channel state information （CSI） obtained by least-squared （LS） estimation is needed in semi-blind estimation. BFGS （Brayben, Fletcher, Goldfarb and Shanno） algorithm, which employs data as well as pilot symbols, estimates the CSI though solving the problem provided by maximum-likelihood （ML） principle. In addition, mean-square-error （MSE） used to evaluate the estimation performance can be further minimized with an optimal pilot design. Simulation results show that the semi-blind estimation achieves a significant improvement in terms of MSE performance over the conventional LS estimation by utilizing data symbols instead of increasing the number of pilot symbols, which demonstrates the estimation accuracy and spectral efficiency are both improved by semiblind estimation for C-RANs.
基金supported in part by the National Natural Science Foundation of China (Grant No. 61222103)the Beijing Natural Science Foundation (Grant No. 4131003)+1 种基金the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP) (Grant No. 20120005140002)the National High Technology Research and Development Program (863 Program) of China under Grant No. 2014AA01A707
文摘The cloud radio access network(C-RAN) has recently been proposed as an important component of the next generation wireless networks providing opportunities for improving both spectral and energy effi ciencies. The performance of this network structure is however constrained by severe inter-cell interference due to the limited capacity of fronthaul between the radio remote heads(RRH) and the base band unit(BBU) pool. To achieve performance improvement taking full advantage of centralized processing capabilities of C-RANs,a set of RRHs can jointly transmit data to the same UE for improved spectral effi ciency. In this paper,a user centralized joint coordinated transmission(UC-JCT) scheme is put forth to investigate the downlink performance of C-RANs. The most important benefit the proposed strategy is the ability to translate what would have been the most dominant interfering sources to usable signal leading to a signifi cantly improved performance. Stochastic geometry is utilized to model the randomness of RRH location and provides a reliable performance analysis. We derive an analytical expression for the closed integral form of the coverage probability of a typical UE. Simulation results confirm the accuracy of our analysis and demonstrate that significant performance gain can be achieved from the proposed coordination schemes.
基金Project supported by the Zhejiang Provincial Natural Science Foundation of China(Nos.LY21F010008 and LD21F010001)the National Natural Science Foundation of China(No.62171412)the Open Research Fund of National Mobile Communications Research Laboratory,Southeast University,China(No.2020D10)。
文摘Owing to the inherent central information processing and resource management ability,the cloud radio access network(C-RAN)is a promising network structure for an intelligent and simplified sixth-generation(6G)wireless network.Nevertheless,to further enhance the capacity and coverage,more radio remote heads(RRHs)as well as high-fidelity and low-latency fronthaul links are required,which may lead to high implementation cost.To address this issue,we propose to exploit the intelligent reflecting surface(IRS)as an alternative way to enhance the C-RAN,which is a low-cost and energy-efficient option.Specifically,we consider the uplink transmission where multi-antenna users communicate with the baseband unit(BBU)pool through multi-antenna RRHs and multiple IRSs are deployed between the users and RRHs.RRHs can conduct either point-to-point(P2P)compression or Wyner-Ziv coding to compress the received signals,which are then forwarded to the BBU pool through fronthaul links.We investigate the joint design and optimization of user transmit beamformers,IRS passive beamformers,and fronthaul compression noise covariance matrices to maximize the uplink sum rate subject to fronthaul capacity constraints under P2P compression and Wyner-Ziv coding.By exploiting the Arimoto-Blahut algorithm and semi-definite relaxation(SDR),we propose a successive convex approximation approach to solve non-convex problems,and two iterative algorithms corresponding to P2P compression and Wyner-Ziv coding are provided.Numerical results verify the performance gain brought about by deploying IRS in C-RAN and the superiority of the proposed joint design.
基金This research was supported by the MSIT(Ministry of Science and ICT),Korea,under the ITRC(Information Technology Research Center)support program(1ITP-2021-2017-0-01633)supervised by the IITP(Institute for Information&communications Technology Planning&Evaluation)This research was supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(NRF-2016R1D1A1B01016322).
文摘The installation of small cells in a 5G network extends the maximum coverage and provides high availability.However,this approach increases the handover overhead in the Core Network(CN)due to frequent handoffs.The variation of user density and movement inside a region of small cells also increases the handover overhead in CN.However,the present 5G system cannot reduce the handover overhead in CN under such circumstances because it relies on a traditionally rigid and complex hierarchical sequence for a handover procedure.Recently,Not Only Stack(NO Stack)architecture has been introduced for Radio Access Network(RAN)to reduce the signaling during handover.This paper proposes a system based on NO Stack architecture and solves the aforementioned problem by adding a dedicated local mobility controller to the edge cloud for each cluster.The dedicated cluster controller manages the user mobility locally inside a cluster and also maintains the forwarding data of a mobile user locally.To reduce the latency for X2-based handover requests,an edge cloud infrastructure has been also developed to provide high-computing for dedicated controllers at the edge of a cellular network.The proposed system is also compared with the traditional 3GPP architecture and other works in the context of overhead and delay caused by X2-based handover requests during user mobility.Simulated results show that the inclusion of a dedicated local controller for small clusters together with the implementation of NO Stack framework reduces the significant amount of overhead of X2-based handover requests at CN.
文摘Cloud computing is the latest major evolution in computing technology. The convergence between cloud computing and tele- com networks could significantly reduce costs and bring new business opportunities for operators. Currently, traditional teleeom operators are embarrassed by the fact that the increase in revenue cannot catch up with the quick growth of users and the expansion of networks. With the introduction of the cloud computing technology, operators can virtualize the network functions through low-cost COTS IT hardware All kinds of existing services can be cloudifled and thus obtain the benefits of statistical multiplexing among IT resources. With the Teleo Cloud architecture, operators can manage both IT infrastructures and network resources intelligently in order to adapt to the dynamic demands from the application and to establish open platforms for developing new services.
