An optimal cooperative beamforming for the amplify-and-forward (AF) MIMO two-way relay channels was designed. Supposing the channel state information (CSI) was perfectly known by the receiver and transmitter as well a...An optimal cooperative beamforming for the amplify-and-forward (AF) MIMO two-way relay channels was designed. Supposing the channel state information (CSI) was perfectly known by the receiver and transmitter as well as the relay, optimal beamforming vectors (matrices) of all nodes were jointly designed based on the criterion of minimizing the sum mean square errors (MSMSE). The analysis result shows that the performance effect of transmitting and receiving beamforming pairs is to maximize the receive signal-to-noise ratio (SNR) at two communication nodes, and the rank of the optimal relay beamforming matrix is no larger than two when there is only one data stream at each source node. A simplified algorithm was put forward to accomplish the design based on the analysis conclusions. Simulation results provide that the system performance, which is characterized in terms of bit error rates (BER), is significantly improved by cooperative beamforming, and the performance of the simplified method is not only very close to the optimal one but also with faster iteration speed and much lower computational complexity.展开更多
The conventional MVDR adaptive beamformer is a high-resolution narrowband beamformer which estimates the optimal beamforming weights using narrowband CSDM of real acoustic field. In practical applications, MVDR algori...The conventional MVDR adaptive beamformer is a high-resolution narrowband beamformer which estimates the optimal beamforming weights using narrowband CSDM of real acoustic field. In practical applications, MVDR algorithm needs long observation time to estimate the covariance matrix. This inherent property makes it difficult to localize fast-moving targets. For wideband signals, MVDR algorithm needs inverting every CSDM which increases the computational demands. For correlated sources, the performance of MVDR will degrade dramatically because the signals will cancel each other. A fast-convergent MVDR algorithm based on subband subarray processing is proposed. The full frequency band is divided into sets of subbands and the line array is divided into sets of subarrays. For every subband the STCM of reduced dimensions is calculated. Then adaptive beamforming weight of fast-convergent MVDR algorithm and spatial spectrum estimation are obtained. At the same time, spatial spectrum estimation can be made for correlated sources using the two-sided spatial smoothing method. Results of simulation and trial data show that the proposed method has high-resolution and near-instantaneous convergence property, two-sided spatial smoothing has satisfactory validity of decorrelation.展开更多
The authors propose a dwindling filter algorithm with Zhou's modified subproblem for nonlinear inequality constrained optimization.The feasibility restoration phase,which is always used in the traditional filter m...The authors propose a dwindling filter algorithm with Zhou's modified subproblem for nonlinear inequality constrained optimization.The feasibility restoration phase,which is always used in the traditional filter method,is not needed.Under mild conditions,global convergence and local superlinear convergence rates are obtained.Numerical results demonstrate that the new algorithm is effective.展开更多
基金Project(60902092)supported by the National Natural Science Foundation of China
文摘An optimal cooperative beamforming for the amplify-and-forward (AF) MIMO two-way relay channels was designed. Supposing the channel state information (CSI) was perfectly known by the receiver and transmitter as well as the relay, optimal beamforming vectors (matrices) of all nodes were jointly designed based on the criterion of minimizing the sum mean square errors (MSMSE). The analysis result shows that the performance effect of transmitting and receiving beamforming pairs is to maximize the receive signal-to-noise ratio (SNR) at two communication nodes, and the rank of the optimal relay beamforming matrix is no larger than two when there is only one data stream at each source node. A simplified algorithm was put forward to accomplish the design based on the analysis conclusions. Simulation results provide that the system performance, which is characterized in terms of bit error rates (BER), is significantly improved by cooperative beamforming, and the performance of the simplified method is not only very close to the optimal one but also with faster iteration speed and much lower computational complexity.
文摘The conventional MVDR adaptive beamformer is a high-resolution narrowband beamformer which estimates the optimal beamforming weights using narrowband CSDM of real acoustic field. In practical applications, MVDR algorithm needs long observation time to estimate the covariance matrix. This inherent property makes it difficult to localize fast-moving targets. For wideband signals, MVDR algorithm needs inverting every CSDM which increases the computational demands. For correlated sources, the performance of MVDR will degrade dramatically because the signals will cancel each other. A fast-convergent MVDR algorithm based on subband subarray processing is proposed. The full frequency band is divided into sets of subbands and the line array is divided into sets of subarrays. For every subband the STCM of reduced dimensions is calculated. Then adaptive beamforming weight of fast-convergent MVDR algorithm and spatial spectrum estimation are obtained. At the same time, spatial spectrum estimation can be made for correlated sources using the two-sided spatial smoothing method. Results of simulation and trial data show that the proposed method has high-resolution and near-instantaneous convergence property, two-sided spatial smoothing has satisfactory validity of decorrelation.
基金supported by the National Natural Science Foundation of China(Nos.11201304,11371253)the Innovation Program of Shanghai Municipal Education Commission(No.12YZ174)the Group of Accounting and Governance Disciplines(No.10kq03)
文摘The authors propose a dwindling filter algorithm with Zhou's modified subproblem for nonlinear inequality constrained optimization.The feasibility restoration phase,which is always used in the traditional filter method,is not needed.Under mild conditions,global convergence and local superlinear convergence rates are obtained.Numerical results demonstrate that the new algorithm is effective.
