基于导频的发射分集OFDM系统的子空间跟踪信道估计
Subspace-Tracking Channel Estimation for Pilot-Symbol-Aided OFDM Systems with Transmitter Diversity
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摘要: 由于发射分集技术可以大大提高系统的抗衰落性能，因此得到了广泛的研究和应用。该文提出了3种基于导频的发射分集正交频分复用(OFDM)系统的子空间幅度跟踪信道估计方法，并分析比较了其估计性能。利用信道传播时延慢变和衰落幅度快变的特点，通过对多径信道的时延子空间和衰落幅度的跟踪，可以部分消除信道估计过程中噪声的影响，大大提高信道估计精度。在信道阶数已知或使用相同秩估计方法的情况下，第3种方法的运算复杂度最低, 性能最好；第1种方法次之，性能最差；第2种方法由于需要进行DFT和IDFT，运算复杂度最高。仿真结果表明，3种子空间幅度跟踪信道估计方法在410-3 误码率时可以提高系统误码率性能1～2 dB左右。Abstract: Transmitter diversity has been studied extensively as a technique for combating channel fading in mobile wireless communications, especially when receiver diversity is expensive or impractical. In this paper, three subspace-tracking channel estimation algorithms for OFDM systems with transmitter diversity are proposed, and their performances are compared. Because the fading channel has slow-varying delays and fast-varying amplitudes, the noise effect in the channel estimation can be partially eliminated by tracking delay subspace and amplitudes of the channel. In three approaches, the last one has the lowest computation complexity and the best performance, the first one has a little high complexity and the worst performance, and the second one has the highest complexity for its DFT and IDFT operations. Simulation results show that one to two decibels benefits can be obtained by subspace and amplitudes tracking.
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Li Ye, Seshadri N, Ariyavisitakul S. Channel estimation for OFDM systems with transmitter diversity in mobile wireless channels. IEEE JSAC, 1999, 17(3): 461.470.[2]Nicoli M, Simeone O, Spagnolini U. Multislot estimation of fast-varying space-time communication channels[J].IEEE Trans. onSignal Processing.2003, 51(5):1184-[3]徐信，蔡跃明, 徐友云. 基于训练序列的发射分集OFDM系统的空时子空间跟踪信道估计[J].电子与信息学报.2005, 27(1):99-浏览[4]Manton J H. Optimal training sequences and pilot tones for OFDM systems[J].IEEE Communications Letters.2001, 5(4):151-[5]Jones V K, Rayleigh G G. Channel estimation for wireless OFDM systems. In Proc. Globecom98, Nov. 1998: 980.985.[6]Stewart G W. Methods of simultaneous iteration for calculating eigenvectors of matrices. In Topics in Numerical Analysis II, J. H. Miller, Ed. New York, 1975: 169.185.[7]Yang B. Projection approximation subspace tracking[J].IEEE Trans. on Signal Processing.1995, 43(1):95-[8]Rabideau D J. Fast, rank adaptive subspace tracking and applications. IEEE Trans. on Signal Processing, 1996, 44(9): 95.107.[9]Strobach P. Low-rank adaptive filter[J].IEEE Trans. on Signal Processing.1996, 44(12):2932-[10]Wax M, Kailath T. Detection of signals by information theoretic criteria. IEEE Trans. on Acoustics, Speech, and Signal Processing, 1985, ASSP-33(2): 387.392.[11]Lindbom L, Sternad M, Ahln A. Tracking of the time-varying mobile radio channels-Part I: the Wiener LMS algorithm[J].IEEE Trans. on Comm.2001, 49(12):2207- -
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