An adaptive MIMO detection algorithm for LTE-A system which is based on sphere detection is proposed in this paper. The proposed algorithm uses M-algorithm for reference to remove unreliable constellation candidates b...An adaptive MIMO detection algorithm for LTE-A system which is based on sphere detection is proposed in this paper. The proposed algorithm uses M-algorithm for reference to remove unreliable constellation candidates before search, and the number of constellation reservation is adaptively adjusted according to SNR. Simulations of LTE-A downlink show that the BER performance of the proposed detection algorithm is nearly the same as maximum likelihood (ML) detection algorithm. However, the complexity is reduced by about 30% compared with full constellation sphere detection.展开更多
To enhance the performance of the artificial bee colony optimization by integrating the quantum computing model into bee colony optimization, we present a quantum-inspired bee colony optimization algorithm. In our met...To enhance the performance of the artificial bee colony optimization by integrating the quantum computing model into bee colony optimization, we present a quantum-inspired bee colony optimization algorithm. In our method, the bees are encoded with the qubits described on the Bloch sphere. The classical bee colony algorithm is used to compute the rotation axes and rotation angles. The Pauli matrices are used to construct the rotation matrices. The evolutionary search is achieved by rotating the qubit about the rotation axis to the target qubit on the Bloch sphere. By measuring with the Pauli matrices, the Bloch coordinates of qubit can be obtained, and the optimization solutions can be presented through the solution space transformation. The proposed method can simultaneously adjust two parameters of a qubit and automatically achieve the best match between two adjustment quantities, which may accelerate the optimization process. The experimental results show that the proposed method is obviously superior to the classical one for some benchmark functions.展开更多
In this paper, we study optimal recovery （reconstruction） of functions on the sphere in the average case setting. We obtain the asymptotic orders of average sampling numbers of a Sobolev space on the sphere with a G...In this paper, we study optimal recovery （reconstruction） of functions on the sphere in the average case setting. We obtain the asymptotic orders of average sampling numbers of a Sobolev space on the sphere with a Gaussian measure in the Lq （S^d-1） metric for 1 ≤ q ≤ ∞, and show that some worst-case asymptotically optimal algorithms are also asymptotically optimal in the average case setting in the Lq （S^d-1） metric for 1 ≤ q ≤ ∞.展开更多
文摘An adaptive MIMO detection algorithm for LTE-A system which is based on sphere detection is proposed in this paper. The proposed algorithm uses M-algorithm for reference to remove unreliable constellation candidates before search, and the number of constellation reservation is adaptively adjusted according to SNR. Simulations of LTE-A downlink show that the BER performance of the proposed detection algorithm is nearly the same as maximum likelihood (ML) detection algorithm. However, the complexity is reduced by about 30% compared with full constellation sphere detection.
文摘To enhance the performance of the artificial bee colony optimization by integrating the quantum computing model into bee colony optimization, we present a quantum-inspired bee colony optimization algorithm. In our method, the bees are encoded with the qubits described on the Bloch sphere. The classical bee colony algorithm is used to compute the rotation axes and rotation angles. The Pauli matrices are used to construct the rotation matrices. The evolutionary search is achieved by rotating the qubit about the rotation axis to the target qubit on the Bloch sphere. By measuring with the Pauli matrices, the Bloch coordinates of qubit can be obtained, and the optimization solutions can be presented through the solution space transformation. The proposed method can simultaneously adjust two parameters of a qubit and automatically achieve the best match between two adjustment quantities, which may accelerate the optimization process. The experimental results show that the proposed method is obviously superior to the classical one for some benchmark functions.
基金supported by the National Natural Science Foundation of China(No.11426179)the National Natural Science Foundation of China(Nos.10871132,11271263)+4 种基金the Key Scientific Research Fund of Xihua University(No.z1312624)the Foundation of Sichuan Educational Committee(No.14ZA0112)the Preeminent Youth Fund for School of Science in Xihua Universitythe Beijing Natural Science Foundation(No.1132001)BCMIIS
文摘In this paper, we study optimal recovery （reconstruction） of functions on the sphere in the average case setting. We obtain the asymptotic orders of average sampling numbers of a Sobolev space on the sphere with a Gaussian measure in the Lq （S^d-1） metric for 1 ≤ q ≤ ∞, and show that some worst-case asymptotically optimal algorithms are also asymptotically optimal in the average case setting in the Lq （S^d-1） metric for 1 ≤ q ≤ ∞.
