An AOR(Accelerated Over-Relaxation)iterative method is suggested by introducing one more parameter than SOR(Successive Over-Relaxation)method for solving coupled Lyapunov matrix equations(CLMEs)that come from continuo...An AOR(Accelerated Over-Relaxation)iterative method is suggested by introducing one more parameter than SOR(Successive Over-Relaxation)method for solving coupled Lyapunov matrix equations(CLMEs)that come from continuous-time Markovian jump linear systems.The proposed algorithm improves the convergence rate,which can be seen from the given illustrative examples.The comprehensive theoretical analysis of convergence and optimal parameter needs further investigation.展开更多
Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at...Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.展开更多
The purpose of this paper is to investigate the preconditioned AOR method with a new preconditioner denoted as I+Sα+SM+Sδfor M-matrix.The new preconditioner is constructed by considering the largest absolute value o...The purpose of this paper is to investigate the preconditioned AOR method with a new preconditioner denoted as I+Sα+SM+Sδfor M-matrix.The new preconditioner is constructed by considering the largest absolute value of the upper triangular part,the secondary diagonal and the last column of the coefficient matrix A.We prove that the rate of the AOR iterative method can be accelerated,and give the comparison with other three preconditioners to show the new pre-conditioner is more effective.Numerical example demonstrates the effectiveness of this preconditioning scheme.展开更多
基金Supported by Key Scientific Research Project of Colleges and Universities in Henan Province of China(Grant No.20B110012)。
文摘An AOR(Accelerated Over-Relaxation)iterative method is suggested by introducing one more parameter than SOR(Successive Over-Relaxation)method for solving coupled Lyapunov matrix equations(CLMEs)that come from continuous-time Markovian jump linear systems.The proposed algorithm improves the convergence rate,which can be seen from the given illustrative examples.The comprehensive theoretical analysis of convergence and optimal parameter needs further investigation.
基金supported by the key project of the National Natural Science Foundation of China (No. 61431001)Huawei Innovation Research Program, the 5G research program of China Mobile Research Institute (Grant No. [2015] 0615)+2 种基金the open research fund of National Mobile Communications Research Laboratory Southeast University (No.2017D02)Key Laboratory of Cognitive Radio and Information Processing, Ministry of Education (Guilin University of Electronic Technology)the Foundation of Beijing Engineering and Technology Center for Convergence Networks and Ubiquitous Services, and Keysight
文摘Massive multiple-input multiple-output(MIMO) system is capable of substantially improving the spectral efficiency as well as the capacity of wireless networks relying on equipping a large number of antenna elements at the base stations. However, the excessively high computational complexity of the signal detection in massive MIMO systems imposes a significant challenge for practical hardware implementations. In this paper, we propose a novel minimum mean square error(MMSE) signal detection using the accelerated overrelaxation(AOR) iterative method without complicated matrix inversion, which is capable of reducing the overall complexity of the classical MMSE algorithm by an order of magnitude. Simulation results show that the proposed AOR-based method can approach the conventional MMSE signal detection with significant complexity reduction.
基金Supported by the Natural Science Foundation of China(2010101GZ30005)Jiangsu Innovation Fund for Doctor of Science(CX07B-027z)
文摘The purpose of this paper is to investigate the preconditioned AOR method with a new preconditioner denoted as I+Sα+SM+Sδfor M-matrix.The new preconditioner is constructed by considering the largest absolute value of the upper triangular part,the secondary diagonal and the last column of the coefficient matrix A.We prove that the rate of the AOR iterative method can be accelerated,and give the comparison with other three preconditioners to show the new pre-conditioner is more effective.Numerical example demonstrates the effectiveness of this preconditioning scheme.
