A new receive antenna subset selection algorithm with low complexity for wireless Multipie-Input Multiple-Output （MIMO） systems is proposed, which is based on the orthogonal components of the channel matrix. Larger ...A new receive antenna subset selection algorithm with low complexity for wireless Multipie-Input Multiple-Output （MIMO） systems is proposed, which is based on the orthogonal components of the channel matrix. Larger capacity is achieved compared with the existing antenna selection methods. Simulation results of quasi-static fiat fading channel demonstrate the significant performance of the proposed selection algorithm.展开更多
For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection ...For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the channel matrix in such a way that the computational complexity of the greedy Joint Transmit/Receive Antenna Selection (JTRAS) algorithm is reduced by a factor of 4n L , where n L is the number of selected antennas. A decoupled version of the proposed algorithm is also proposed to further improve the efficiency of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the performance of the proposed approaches are evaluated mathematically and verified by computer simulations. The results have shown that the proposed joint antenna selection algorithm maintains the capacity perormance of the JTRAS algorithm while its computational complexity is only 1/4n L of that of the JTRAS algorithm. The decoupled version of the proposed algorithm further reduces the computational complexity of the joint antenna selection and has better performance than other decoupling-based algorithms when the selected antenna subset is small as compared to the total number of antennas.展开更多
基金Supported by the National Natural Science Foundation of China (605772105)Open Foundations of the State Key Laboratory of Mobile Communications (A0401, A200508)+1 种基金the State Key Lab of Integrated Services Networks (ISN7-02)the Program for New Century Ex-cellent Talents (NCET) in University.
文摘A new receive antenna subset selection algorithm with low complexity for wireless Multipie-Input Multiple-Output （MIMO） systems is proposed, which is based on the orthogonal components of the channel matrix. Larger capacity is achieved compared with the existing antenna selection methods. Simulation results of quasi-static fiat fading channel demonstrate the significant performance of the proposed selection algorithm.
文摘For reducing the computational complexity of the problem of joint transmit and receive antenna selection in Multiple-Input-Multiple-Output (MIMO) systems, we present a concise joint transmit/receive antenna selection algorithm. Using a novel partition of the channel matrix, we drive a concise formula. This formula enables us to augment the channel matrix in such a way that the computational complexity of the greedy Joint Transmit/Receive Antenna Selection (JTRAS) algorithm is reduced by a factor of 4n L , where n L is the number of selected antennas. A decoupled version of the proposed algorithm is also proposed to further improve the efficiency of the JTRAS algorithm, with some capacity degradation as a tradeoff. The computational complexity and the performance of the proposed approaches are evaluated mathematically and verified by computer simulations. The results have shown that the proposed joint antenna selection algorithm maintains the capacity perormance of the JTRAS algorithm while its computational complexity is only 1/4n L of that of the JTRAS algorithm. The decoupled version of the proposed algorithm further reduces the computational complexity of the joint antenna selection and has better performance than other decoupling-based algorithms when the selected antenna subset is small as compared to the total number of antennas.
