Necessary and sufficient conditions are given for the existence of the general solution, the centrosymmetric solution, and the centroskewsymmetric solution to a system of linear matrix equations over an arbitrary skew...Necessary and sufficient conditions are given for the existence of the general solution, the centrosymmetric solution, and the centroskewsymmetric solution to a system of linear matrix equations over an arbitrary skew field. The representations of such the solutions of the system are also derived.展开更多
Let P be a property referring to a real matrix. For a sign pattern A, if there exists a real matrix B in the qualitative class of A such that B has property P, then we say A allows P. Three cases that A allows an M m...Let P be a property referring to a real matrix. For a sign pattern A, if there exists a real matrix B in the qualitative class of A such that B has property P, then we say A allows P. Three cases that A allows an M matrix, an inverse M matrix and a P 0 matrix are considered. The complete characterizations are obtained.展开更多
Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection a...Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection and precoding. Recently, many detection and precoding methods were proposed using approximate iteration methods, which meet the demand of precision with low complexity. In this paper, we compare these approximate iteration methods in precision and complexity, and then improve these methods with iteration refinement at the cost of little complexity and no extra hardware resource. By derivation, our proposal is a combination of three approximate iteration methods in essence and provides remarkable precision improvement on desired vectors. The results show that our proposal provides 27%-83% normalized mean-squared error improvement of the detection symbol vector and precoding symbol vector. Moreover, we find the bit-error rate is mainly controlled by soft-input soft-output Viterbi decoding when using approximate iteration methods. Further, only considering the effect on soft-input soft-output Viterbi decoding, the simulation results show that using a rough estimation for the filter matrix of minimum mean square error detection to calculating log-likelihood ratio could provideenough good bit-error rate performance, especially when the ratio of base station antennas number and the users number is not too large.展开更多
基金Supported by the National Natural Science Foundation of China(10471085)
文摘Necessary and sufficient conditions are given for the existence of the general solution, the centrosymmetric solution, and the centroskewsymmetric solution to a system of linear matrix equations over an arbitrary skew field. The representations of such the solutions of the system are also derived.
文摘Let P be a property referring to a real matrix. For a sign pattern A, if there exists a real matrix B in the qualitative class of A such that B has property P, then we say A allows P. Three cases that A allows an M matrix, an inverse M matrix and a P 0 matrix are considered. The complete characterizations are obtained.
文摘Massive multiple-input multiple-output provides improved energy efficiency and spectral efficiency in 5 G. However it requires large-scale matrix computation with tremendous complexity, especially for data detection and precoding. Recently, many detection and precoding methods were proposed using approximate iteration methods, which meet the demand of precision with low complexity. In this paper, we compare these approximate iteration methods in precision and complexity, and then improve these methods with iteration refinement at the cost of little complexity and no extra hardware resource. By derivation, our proposal is a combination of three approximate iteration methods in essence and provides remarkable precision improvement on desired vectors. The results show that our proposal provides 27%-83% normalized mean-squared error improvement of the detection symbol vector and precoding symbol vector. Moreover, we find the bit-error rate is mainly controlled by soft-input soft-output Viterbi decoding when using approximate iteration methods. Further, only considering the effect on soft-input soft-output Viterbi decoding, the simulation results show that using a rough estimation for the filter matrix of minimum mean square error detection to calculating log-likelihood ratio could provideenough good bit-error rate performance, especially when the ratio of base station antennas number and the users number is not too large.
