针对高速铁路LTE-R(long term evolution for mobile communications-railway)越区切换过程中,基于A3事件判决的越区切换算法容易出现乒乓切换频繁和切换成功率较低的问题,提出了基于改进的模糊预测优化切换算法。该算法对切换过程中的...针对高速铁路LTE-R(long term evolution for mobile communications-railway)越区切换过程中,基于A3事件判决的越区切换算法容易出现乒乓切换频繁和切换成功率较低的问题,提出了基于改进的模糊预测优化切换算法。该算法对切换过程中的参考信号接收功率(RSRP)进行采集,并通过改进的GM(1,1)灰色预测算法对采集的RSRP值进行优化处理,处理之后的测量参数值经3次循环预测和加权平均后,被送入判决公式进行判决。在MATLAB上的仿真结果表明所提算法降低了切换过程中的参数波动值,从而减少了乒乓切换的次数,提高了越区切换的成功率。展开更多
A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a...A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.展开更多
文摘针对高速铁路LTE-R(long term evolution for mobile communications-railway)越区切换过程中,基于A3事件判决的越区切换算法容易出现乒乓切换频繁和切换成功率较低的问题,提出了基于改进的模糊预测优化切换算法。该算法对切换过程中的参考信号接收功率(RSRP)进行采集,并通过改进的GM(1,1)灰色预测算法对采集的RSRP值进行优化处理,处理之后的测量参数值经3次循环预测和加权平均后,被送入判决公式进行判决。在MATLAB上的仿真结果表明所提算法降低了切换过程中的参数波动值,从而减少了乒乓切换的次数,提高了越区切换的成功率。
基金Supported by the National Natural Science Foundation for Outstanding Youth(61422102)
文摘A robust finite-horizon Kalman filter is designed for linear discrete-time systems subject to norm-bounded uncertainties in the modeling parameters and missing measurements.The missing measurements were described by a binary switching sequence satisfying a conditional probability distribution,the commonest cases in engineering,such that the expectation of the measurements could be utilized during the iteration process.To consider the uncertainties in the system model,an upperbound for the estimation error covariance was obtained since its real value was unaccessible.Our filter scheme is on the basis of minimizing the obtained upper bound where we refer to the deduction of a classic Kalman filter thus calculation of the derivatives are avoided.Simulations are presented to illustrate the effectiveness of the proposed approach.
