In this paper, we study the performance of block diagonalization (BD) scheme for a downlink multiuser multi-input multi-output (MIMO) system with imperfect channel state information (CSI). At each mobile user, informa...In this paper, we study the performance of block diagonalization (BD) scheme for a downlink multiuser multi-input multi-output (MIMO) system with imperfect channel state information (CSI). At each mobile user, information about the channel is obtained by applying the minimum mean-square-error (MMSE) channel estimation method. The channel state information is fed back to the base station through error-free uplink channels. A theoretical analysis is performed showing that channel estimation errors contribute to co-channel interferences thus deteriorating sum rate capacity. Computer simulations are performed to evaluate the impact of channel estimation errors on the sum rate capacity. The results show that if the MSE of the channel estimation is not less than 10-2, the impact of channel estimation errors is significant and cannot be neglected. To combat this adverse effect, a proper transmit power level is required for the training signals.展开更多
The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field...The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field determination. On the basis of block-diagonal least squares method, three data processing strategies are employed to determine the gravity field models using three kinds of simulated global grid data with different noise spatial distri- bution in this paper. The numerical results show that when we employed the weight matrix corresponding to the noise of the observation data, the model computed by the least squares using the full normal matrix has much higher precision than the one estimated only using the block part of the normal matrix. The model computed by the block-diagonal least squares method without the weight matrix has slightly lower precision than the model computed using the rigorous least squares with the weight matrix. The result offers valuable reference to the using of block-diagonal least squares method in ultra-high gravity model determination.展开更多
We investigate the sum capacity of Block Diagonalization precoding Multiple Input Mul-tiple Output Broadcast Channels(BD MIMO BC) with imperfect Channel State Information(CSI) at the base station.Since it is difficult...We investigate the sum capacity of Block Diagonalization precoding Multiple Input Mul-tiple Output Broadcast Channels(BD MIMO BC) with imperfect Channel State Information(CSI) at the base station.Since it is difficult to obtain the exact expression,a lower and an upper bounds of the sum capacity under Gaussian channel estimation errors are drived instead.Analyses show that the gap between two bounds is considerably tight at all Signal to Noise Ratio(SNR) region.From the lower bound of the sum capacity,we can see that the multiplexing gain tends to be zero at high SNR region,which indicates that the BD MIMO BC system with channel estimation errors is interference-limited at high SNR.展开更多
块对角化(block diagonalization,BD)算法是一种多输入多输出的传统线性预编码算法,其核心思想是通过奇异值分解(singular value decomposition,SVD)找到干扰矩阵零空间的正交基,从而完全消除多用户干扰(multiuser interference,MUI),...块对角化(block diagonalization,BD)算法是一种多输入多输出的传统线性预编码算法,其核心思想是通过奇异值分解(singular value decomposition,SVD)找到干扰矩阵零空间的正交基,从而完全消除多用户干扰(multiuser interference,MUI),但是随着收发端数目的增多,BD预编码算法所需的计算复杂也大大增加,成为了制约其发展的关键因素之一.为此,本文提出了一种改进的低复杂度BD算法——基于正交分解中的施密特正交化求逆与格基规约操作的组合算法,对传统BD算法两次高复杂度操作的奇异值分解用施密特正交化和格基规约操作进行替换,从而降低算法复杂度.结果表明,本文改进算法的计算复杂度上降低了46.7%,系统和容量上得到了2–10 bits/Hz的提高,同时误码率上得到了2个量级的优化.展开更多
User selection is necessary for multiuser multiple-input multiple-output(MIMO) downlink systems with block diagonalization(BD) due to the limited free spatial transmit dimensions.The pure user selection algorithms can...User selection is necessary for multiuser multiple-input multiple-output(MIMO) downlink systems with block diagonalization(BD) due to the limited free spatial transmit dimensions.The pure user selection algorithms can be improved by performing receive antenna selection(RAS) to increase sum rate.In this paper,a joint user and antenna selection algorithm,which performs user selection for sum rate maximization in the first stage and then performs antenna selection in the second stage,is proposed.The antenna selection process alternately drops one antenna with the poorest channel quality based on maximum determinant ranking(MDR) from the users selected during the first stage and activates one antenna with the maximum norm of projected channel from the remaining users.Simulation results show that the proposed algorithm significantly outperforms the algorithm only performing user selection as well as the algorithm combining user selection with MDR receive antenna selection in terms of sum rate.展开更多
In multi-cell cooperative multi-input multi-output （MIMO） systems, base station （BS） can exchange and utilize channel state information （CSI） of adjacent cell users to manage co-channel interference. Users quant...In multi-cell cooperative multi-input multi-output （MIMO） systems, base station （BS） can exchange and utilize channel state information （CSI） of adjacent cell users to manage co-channel interference. Users quantize the CSIs of desired channel and interference channels using finite-rate feedback links, then BS can generate cooperative block diagonalization （BD） precoding matrices using the obtained quantized CSI at transmitter to supress co-channel interference. In this paper, a novel adaptive bit allocation scheme is proposed to minimize the rate loss due to imperfect CSI. We derive the closed-form expression of rate loss caused by both channel delay and limited feedback. Based on the derived rate loss expression, the proposed scheme can adaptively allocate more bits to quantize the better channels with smaller delays and fewer bits to worse channels with larger delays. Simulation results show that the proposed scheme yields higher performance than other allocation schemes.展开更多
文摘In this paper, we study the performance of block diagonalization (BD) scheme for a downlink multiuser multi-input multi-output (MIMO) system with imperfect channel state information (CSI). At each mobile user, information about the channel is obtained by applying the minimum mean-square-error (MMSE) channel estimation method. The channel state information is fed back to the base station through error-free uplink channels. A theoretical analysis is performed showing that channel estimation errors contribute to co-channel interferences thus deteriorating sum rate capacity. Computer simulations are performed to evaluate the impact of channel estimation errors on the sum rate capacity. The results show that if the MSE of the channel estimation is not less than 10-2, the impact of channel estimation errors is significant and cannot be neglected. To combat this adverse effect, a proper transmit power level is required for the training signals.
基金supported by the National Natural Science Foundation of China for Distinguished Young Scholars (41404028)
文摘The block-diagonal least squares method, which theoretically has specific requirements for the observation data and the spatial distribution of its precision, plays an important role in ultra-high degree gravity field determination. On the basis of block-diagonal least squares method, three data processing strategies are employed to determine the gravity field models using three kinds of simulated global grid data with different noise spatial distri- bution in this paper. The numerical results show that when we employed the weight matrix corresponding to the noise of the observation data, the model computed by the least squares using the full normal matrix has much higher precision than the one estimated only using the block part of the normal matrix. The model computed by the block-diagonal least squares method without the weight matrix has slightly lower precision than the model computed using the rigorous least squares with the weight matrix. The result offers valuable reference to the using of block-diagonal least squares method in ultra-high gravity model determination.
基金Supported by Chinese 863 Program (2006AA01Z268)the National Natural Science Foundation of China (No. 60496311)
文摘We investigate the sum capacity of Block Diagonalization precoding Multiple Input Mul-tiple Output Broadcast Channels(BD MIMO BC) with imperfect Channel State Information(CSI) at the base station.Since it is difficult to obtain the exact expression,a lower and an upper bounds of the sum capacity under Gaussian channel estimation errors are drived instead.Analyses show that the gap between two bounds is considerably tight at all Signal to Noise Ratio(SNR) region.From the lower bound of the sum capacity,we can see that the multiplexing gain tends to be zero at high SNR region,which indicates that the BD MIMO BC system with channel estimation errors is interference-limited at high SNR.
基金the National Science and Technology Major Project (No.2009ZX03002-003)
文摘User selection is necessary for multiuser multiple-input multiple-output(MIMO) downlink systems with block diagonalization(BD) due to the limited free spatial transmit dimensions.The pure user selection algorithms can be improved by performing receive antenna selection(RAS) to increase sum rate.In this paper,a joint user and antenna selection algorithm,which performs user selection for sum rate maximization in the first stage and then performs antenna selection in the second stage,is proposed.The antenna selection process alternately drops one antenna with the poorest channel quality based on maximum determinant ranking(MDR) from the users selected during the first stage and activates one antenna with the maximum norm of projected channel from the remaining users.Simulation results show that the proposed algorithm significantly outperforms the algorithm only performing user selection as well as the algorithm combining user selection with MDR receive antenna selection in terms of sum rate.
基金supported by the Important National Science & Technology Specific Projects(2010ZX03005-001-0)the Hi-Tech Research and Development of China(2006AA01Z272)the New Century Excellent Talents in University(NCET):(NCET-11-0593)
文摘In multi-cell cooperative multi-input multi-output （MIMO） systems, base station （BS） can exchange and utilize channel state information （CSI） of adjacent cell users to manage co-channel interference. Users quantize the CSIs of desired channel and interference channels using finite-rate feedback links, then BS can generate cooperative block diagonalization （BD） precoding matrices using the obtained quantized CSI at transmitter to supress co-channel interference. In this paper, a novel adaptive bit allocation scheme is proposed to minimize the rate loss due to imperfect CSI. We derive the closed-form expression of rate loss caused by both channel delay and limited feedback. Based on the derived rate loss expression, the proposed scheme can adaptively allocate more bits to quantize the better channels with smaller delays and fewer bits to worse channels with larger delays. Simulation results show that the proposed scheme yields higher performance than other allocation schemes.
