在大规模多输入多输出系统中,最小均方误差(minimum mean square error,MMSE)算法能达到接近最优的线性信号检测性能,但是MMSE算法需要复杂的矩阵求逆运算,这限制了该算法的应用。为了降低运算复杂度,改进MMSE算法,利用Barzilai-Borwein...在大规模多输入多输出系统中,最小均方误差(minimum mean square error,MMSE)算法能达到接近最优的线性信号检测性能,但是MMSE算法需要复杂的矩阵求逆运算,这限制了该算法的应用。为了降低运算复杂度,改进MMSE算法,利用Barzilai-Borwein(BB)迭代算法来避免矩阵求逆运算,提出了结构简单的BB迭代信号检测算法,且基于信道硬化特性进一步优化了迭代初始解以加快算法的收敛速度。理论和仿真结果表明,所提出的BB迭代算法的性能优于最近提出的Neumann级数展开算法,而其复杂度相比截短阶数i=3的Neumann级数展开算法减少了一个数量级;且该算法收敛速度较快,在给定初始值的条件下,通过简单的几次迭代,能够快速接近MMSE算法的检测性能。展开更多
针对时间反演多址系统中信道的相关性会导致多用户干扰的问题,以降低用户间干扰和算法复杂度为目标,提出基于Barzilai-Borwein的共轭梯度迭代检测算法。首先通过共轭梯度迭代两次找到最速下降方向,然后通过Barzilai-Borwein沿着共轭梯...针对时间反演多址系统中信道的相关性会导致多用户干扰的问题,以降低用户间干扰和算法复杂度为目标,提出基于Barzilai-Borwein的共轭梯度迭代检测算法。首先通过共轭梯度迭代两次找到最速下降方向,然后通过Barzilai-Borwein沿着共轭梯度搜索的方向继续迭代。仿真表明,所提算法收敛速度快于Barzilai-Borwein和共轭梯度算法,且复杂度低于共轭梯度算法和最小均方误差(minimum mean square error,MMSE)算法,保持在O(N2)。展开更多
目的:为了保持大规模MIMO系统上行链路信号高检测性能同时降低实现复杂度。方法:在信号检测中,传统最小均方误差(MMSE,minimum mean square error)算法可以获得近似最优检测性能,但需要高维矩阵求逆,复杂度很高。本文通过在最速下降法和...目的:为了保持大规模MIMO系统上行链路信号高检测性能同时降低实现复杂度。方法:在信号检测中,传统最小均方误差(MMSE,minimum mean square error)算法可以获得近似最优检测性能,但需要高维矩阵求逆,复杂度很高。本文通过在最速下降法和Barzilai-Borwein迭代算法结合基础上,采用Richardson算法初始值,在此基础上对步长合理选取,提出一种改进Barzilai-Borwein信号检测方法。结果:该算法相对于MMSE复杂度降低一个数量级,并且算法误码率性能又可以与MMSE算法相当,同时该算法相对于Barzilai-Borwein和CBB(Cauchy Barzilai-Borwein)检测,复杂度提升很少,但性能有较大提升。结论:基于改进修正Barzilai-Borwein迭代大规模MIMO信号检测算法只需4次迭代就可接近MMSE,在保持高检测性能的同时实现了复杂度降低。展开更多
Due to its simplicity and efficiency,the Barzilai and Borwein(BB)gradi-ent method has received various attentions in different fields.This paper presents a new analysis of the BB method for two-dimensional strictly co...Due to its simplicity and efficiency,the Barzilai and Borwein(BB)gradi-ent method has received various attentions in different fields.This paper presents a new analysis of the BB method for two-dimensional strictly convex quadratic func-tions.The analysis begins with the assumption that the gradient norms at the first two iterations are fixed.We show that there is a superlinear convergence step in at most three consecutive steps.Meanwhile,we provide a better convergence relation for the BB method.The influence of the starting point and the condition number to the convergence rate is comprehensively addressed.展开更多
In this paper, a new trust region method with simple model for solving large-scale unconstrained nonlinear optimization is proposed. By employing the generalized weak quasi-Newton equations, we derive several schemes ...In this paper, a new trust region method with simple model for solving large-scale unconstrained nonlinear optimization is proposed. By employing the generalized weak quasi-Newton equations, we derive several schemes to construct variants of scalar matrices as the Hessian approximation used in the trust region subproblem. Under some reasonable conditions, global convergence of the proposed algorithm is established in the trust region framework. The numerical experiments on solving the test problems with dimensions from 50 to 20,000 in the CUTEr library are reported to show efficiency of the algorithm.展开更多
This paper proposes a direct search frame-based adaptive Barzilai-Borwein method for unconstrained minimization. The method is based on the framework of frame-based algorithms proposed by Coope and Price, but we use t...This paper proposes a direct search frame-based adaptive Barzilai-Borwein method for unconstrained minimization. The method is based on the framework of frame-based algorithms proposed by Coope and Price, but we use the strategy of ABB method and the rotational minimal positive basis to reduce the computation work at each iteration. Under some mild assumptions, the convergence of this approach will be established. Through five hundreds and twenty numerical tests using the CUTEr test problem library, we show that the proposed method is promising.展开更多
文摘在大规模多输入多输出系统中,最小均方误差(minimum mean square error,MMSE)算法能达到接近最优的线性信号检测性能,但是MMSE算法需要复杂的矩阵求逆运算,这限制了该算法的应用。为了降低运算复杂度,改进MMSE算法,利用Barzilai-Borwein(BB)迭代算法来避免矩阵求逆运算,提出了结构简单的BB迭代信号检测算法,且基于信道硬化特性进一步优化了迭代初始解以加快算法的收敛速度。理论和仿真结果表明,所提出的BB迭代算法的性能优于最近提出的Neumann级数展开算法,而其复杂度相比截短阶数i=3的Neumann级数展开算法减少了一个数量级;且该算法收敛速度较快,在给定初始值的条件下,通过简单的几次迭代,能够快速接近MMSE算法的检测性能。
文摘针对时间反演多址系统中信道的相关性会导致多用户干扰的问题,以降低用户间干扰和算法复杂度为目标,提出基于Barzilai-Borwein的共轭梯度迭代检测算法。首先通过共轭梯度迭代两次找到最速下降方向,然后通过Barzilai-Borwein沿着共轭梯度搜索的方向继续迭代。仿真表明,所提算法收敛速度快于Barzilai-Borwein和共轭梯度算法,且复杂度低于共轭梯度算法和最小均方误差(minimum mean square error,MMSE)算法,保持在O(N2)。
文摘目的:为了保持大规模MIMO系统上行链路信号高检测性能同时降低实现复杂度。方法:在信号检测中,传统最小均方误差(MMSE,minimum mean square error)算法可以获得近似最优检测性能,但需要高维矩阵求逆,复杂度很高。本文通过在最速下降法和Barzilai-Borwein迭代算法结合基础上,采用Richardson算法初始值,在此基础上对步长合理选取,提出一种改进Barzilai-Borwein信号检测方法。结果:该算法相对于MMSE复杂度降低一个数量级,并且算法误码率性能又可以与MMSE算法相当,同时该算法相对于Barzilai-Borwein和CBB(Cauchy Barzilai-Borwein)检测,复杂度提升很少,但性能有较大提升。结论:基于改进修正Barzilai-Borwein迭代大规模MIMO信号检测算法只需4次迭代就可接近MMSE,在保持高检测性能的同时实现了复杂度降低。
基金This work was partly supported by the Chinese NSF grants(Nos.10831106 and 81173633)the CAS grant(No.kjcx-yw-s7-03)the China National Funds for Distinguished Young Scientists(No.11125107).
文摘Due to its simplicity and efficiency,the Barzilai and Borwein(BB)gradi-ent method has received various attentions in different fields.This paper presents a new analysis of the BB method for two-dimensional strictly convex quadratic func-tions.The analysis begins with the assumption that the gradient norms at the first two iterations are fixed.We show that there is a superlinear convergence step in at most three consecutive steps.Meanwhile,we provide a better convergence relation for the BB method.The influence of the starting point and the condition number to the convergence rate is comprehensively addressed.
基金supported by National Natural Science Foundation of China (Grant Nos. 11571178, 11401308, 11371197 and 11471145)the National Science Foundation of USA (Grant No. 1522654)a Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘In this paper, a new trust region method with simple model for solving large-scale unconstrained nonlinear optimization is proposed. By employing the generalized weak quasi-Newton equations, we derive several schemes to construct variants of scalar matrices as the Hessian approximation used in the trust region subproblem. Under some reasonable conditions, global convergence of the proposed algorithm is established in the trust region framework. The numerical experiments on solving the test problems with dimensions from 50 to 20,000 in the CUTEr library are reported to show efficiency of the algorithm.
基金Acknowledgments. This work was supported by the National Natural Science Founda- tion of China （11071117, 11274109） and the Natural Science Foundation of Jiangsu Province （BK20141409）.
文摘This paper proposes a direct search frame-based adaptive Barzilai-Borwein method for unconstrained minimization. The method is based on the framework of frame-based algorithms proposed by Coope and Price, but we use the strategy of ABB method and the rotational minimal positive basis to reduce the computation work at each iteration. Under some mild assumptions, the convergence of this approach will be established. Through five hundreds and twenty numerical tests using the CUTEr test problem library, we show that the proposed method is promising.
