Linearly time-varying channel estimation and training power allocation for OFDM/MIMO systems using superimposed training  

作　　者：ZHANG Han DAI XianHua Pan DaRu 

机构地区：[1]School of Physics and Telecommunication Engineering, South China Normal University Guangzhou 510006, China [2]Department of Information Science and Technology, SUN Yat-sen University, Guangzhou 510026, China

出　　处：《Science China(Information Sciences)》2011年第7期1456-1470,共15页中国科学（信息科学）（英文版）

基　　金：supported by the National Natural Science Foundation of China (Grant No.61002012);the Project of NSF of Guangdong Province (Grant No.10451063101006074);the Industry-Universities-Research Cooperation Project of Guangdong Province and Ministry of Education of China (Grant No.2007A090302116)

摘　　要：We address the problem of estimating the linearly time-varying （LTV） channel of orthogonal frequency division multiplexing （OFDM）/multiple-input multiple-output （MIMO） systems using superimposed training （ST）. The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present performance analysis of the channel estimation and derive a closed-form expression for the ehannel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.We address the problem of estimating the linearly time-varying （LTV） channel of orthogonal frequency division multiplexing （OFDM）/multiple-input multiple-output （MIMO） systems using superimposed training （ST）. The LTV channel is modeled by truncated discrete Fourier bases. Based on this model, a two-step approach is adopted to estimate the LTV channel over multiple OFDM symbols. We also present performance analysis of the channel estimation and derive a closed-form expression for the ehannel estimation variances. It is shown that the estimation variances, unlike that of the conventional ST-based schemes, approach to a fixed lower-bound as the training length increases, which is directly proportional to information-pilot power ratios. For wireless communication systems with a limited transmission power, we optimize the ST power allocation by maximizing the lower bound of the average channel capacity. Simulation results show that the proposed approach outperforms the frequency-division multiplexed training schemes.

关 键 词：OFDM/MIMO systems linearly time-varying channel estimation superimposed training training power allocation 

分 类 号：TN929.533[电子电信—通信与信息系统] TP273[电子电信—信息与通信工程]