In this paper,a quasi-Newton method for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks(C-RANs).Different from traditional pilot-aided estimation,semi-blind estimation uti...In this paper,a quasi-Newton method for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks(C-RANs).Different from traditional pilot-aided estimation,semi-blind 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 maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are ...The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.展开更多
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 for semi-blind estimation is derived for channel estimation in uplink cloud radio access networks(C-RANs).Different from traditional pilot-aided estimation,semi-blind 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 by the National Natural Science Foundation of China (Nos. 51279186, 51479183, 51509227)the Shandong Province Natural Science Foundation, China (No. ZR2014EEQ030)the Fundamental Research Funds for the Central Universities (No. 201413003)
文摘The maximum entropy distribution, which consists of various recognized theoretical distributions, is a better curve to estimate the design thickness of sea ice. Method of moment and empirical curve fitting method are common-used parameter estimation methods for maximum entropy distribution. In this study, we propose to use the particle swarm optimization method as a new parameter estimation method for the maximum entropy distribution, which has the advantage to avoid deviation introduced by simplifications made in other methods. We conducted a case study to fit the hindcasted thickness of the sea ice in the Liaodong Bay of Bohai Sea using these three parameter-estimation methods for the maximum entropy distribution. All methods implemented in this study pass the K-S tests at 0.05 significant level. In terms of the average sum of deviation squares, the empirical curve fitting method provides the best fit for the original data, while the method of moment provides the worst. Among all three methods, the particle swarm optimization method predicts the largest thickness of the sea ice for a same return period. As a result, we recommend using the particle swarm optimization method for the maximum entropy distribution for offshore structures mainly influenced by the sea ice in winter, but using the empirical curve fitting method to reduce the cost in the design of temporary and economic buildings.
