Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which ent...Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.展开更多
This paper presents a novel robust S transform algorithm based on the clipping method to process signals corrupted by impulsive noise.The proposed algorithm is introduced to determine the clipping threshold value acco...This paper presents a novel robust S transform algorithm based on the clipping method to process signals corrupted by impulsive noise.The proposed algorithm is introduced to determine the clipping threshold value according to the characteristics of the signal samples.Signals in various impulsive noise models are considered to illustrate that the robust S transform can achieve better performance than the standard S transform.Moreover,mean square errors for instantaneous frequency estimation of the robust S transform are compared with that of the standard S transform,showing that the robust S transform can achieve significantly improved instantaneous frequency estimation for the signals in impulsive noise.展开更多
为了消除三轴磁传感器自身的误差,针对其存在的偏移误差、灵敏度误差和非正交误差的特点,建立三轴磁传感器的误差校正模型,利用批量最小二乘拟合方法提出相应的磁传感器校正方法,不需要额外的加速计辅助即可对三轴磁传感器进行校正,并...为了消除三轴磁传感器自身的误差,针对其存在的偏移误差、灵敏度误差和非正交误差的特点,建立三轴磁传感器的误差校正模型,利用批量最小二乘拟合方法提出相应的磁传感器校正方法,不需要额外的加速计辅助即可对三轴磁传感器进行校正,并通过磁传感器的误差校正实验进行验证。校正实验结果表明,该三轴磁传感器校正后的均方根误差减小到103 n T,磁传感器的校正方法可以有效消除自身的误差,并且不需要其他辅助手段。展开更多
基金supported by National Natural Science Foundation of China(62371225,62371227)。
文摘Linear minimum mean square error(MMSE)detection has been shown to achieve near-optimal performance for massive multiple-input multiple-output(MIMO)systems but inevitably involves complicated matrix inversion,which entails high complexity.To avoid the exact matrix inversion,a considerable number of implicit and explicit approximate matrix inversion based detection methods is proposed.By combining the advantages of both the explicit and the implicit matrix inversion,this paper introduces a new low-complexity signal detection algorithm.Firstly,the relationship between implicit and explicit techniques is analyzed.Then,an enhanced Newton iteration method is introduced to realize an approximate MMSE detection for massive MIMO uplink systems.The proposed improved Newton iteration significantly reduces the complexity of conventional Newton iteration.However,its complexity is still high for higher iterations.Thus,it is applied only for first two iterations.For subsequent iterations,we propose a novel trace iterative method(TIM)based low-complexity algorithm,which has significantly lower complexity than higher Newton iterations.Convergence guarantees of the proposed detector are also provided.Numerical simulations verify that the proposed detector exhibits significant performance enhancement over recently reported iterative detectors and achieves close-to-MMSE performance while retaining the low-complexity advantage for systems with hundreds of antennas.
基金supported by the National Natural Science Foundation of China(6110216461272224)the Scientific Research Fund of Hangzhou Normal University(2011QDL021)
文摘This paper presents a novel robust S transform algorithm based on the clipping method to process signals corrupted by impulsive noise.The proposed algorithm is introduced to determine the clipping threshold value according to the characteristics of the signal samples.Signals in various impulsive noise models are considered to illustrate that the robust S transform can achieve better performance than the standard S transform.Moreover,mean square errors for instantaneous frequency estimation of the robust S transform are compared with that of the standard S transform,showing that the robust S transform can achieve significantly improved instantaneous frequency estimation for the signals in impulsive noise.
文摘为了消除三轴磁传感器自身的误差,针对其存在的偏移误差、灵敏度误差和非正交误差的特点,建立三轴磁传感器的误差校正模型,利用批量最小二乘拟合方法提出相应的磁传感器校正方法,不需要额外的加速计辅助即可对三轴磁传感器进行校正,并通过磁传感器的误差校正实验进行验证。校正实验结果表明,该三轴磁传感器校正后的均方根误差减小到103 n T,磁传感器的校正方法可以有效消除自身的误差,并且不需要其他辅助手段。
