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Semiblind Channel Estimation for Multiuser MIMO-CDMA Systems with Orthogonal Space-Time Block Codes

机译:具有正交空时分组码的多用户MIMO-CDMA系统的半盲信道估计

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In this paper, we concern the channel estimation for a wireless communication system in which the techniques of multiple-input multiple-output, code division multiple access (CDMA) and orthogonal space-time block codes (OSTBCs) are integrated together for the purpose of achieving high data rate. We show that a composite channel information (CCI) vector can be formed, which contains the effects of channel state information, spreading coding and OSTBCs. From the standpoint of the Multiple Signal Classification method, such CCI vector must lie in the signal subspace spanned by the dominant eigenvectors of the received data covariance matrix. Also, this CCI vector is located in another subspace which is associated with the CDMA and OSTBC codes and can be computed off-line. Using the vector space projections method, this CCI vector can be viewed as the intersection of these two subspaces and thus can be computed by alternative projections. In order to reduce the computation complexity, we propose an equivalent but computationally effective single-step solution in which the channel estimation amounts to searching for the principal eigenvector of a certain matrix with moderate size. Additionally, only one training block is required to overcome the problem of sign ambiguity. Numerical results demonstrate that, in addition to improving the bandwidth efficiency, the proposed method offers better performance in terms of channel estimation accuracy and bit-error-rate as compared with the standard nonblind least-squares channel estimation approach.
机译:在本文中,我们关注无线通信系统中的信道估计,在该系统中,为了实现以下目的,将多输入多输出,码分多址(CDMA)和正交空时分组码(OSTBC)技术集成在一起实现高数据速率。我们表明可以形成一个复合信道信息(CCI)向量,其中包含信道状态信息,扩频编码和OSTBC的影响。从多信号分类方法的角度来看,这种CCI向量必须位于由接收数据协方差矩阵的主要特征向量所跨越的信号子空间中。而且,该CCI矢量位于与CDMA和OSTBC码相关联的另一个子空间中,并且可以离线计算。使用向量空间投影方法,可以将此CCI向量视为这两个子空间的交集,因此可以通过替代投影来计算。为了降低计算复杂度,我们提出了一种等效但在计算上有效的单步解决方案,其中,信道估计等于搜索具有中等大小的某个矩阵的主特征向量。另外,只需要一个训练块就可以解决符号模糊的问题。数值结果表明,与标准的非盲最小二乘信道估计方法相比,该方法除了提高带宽效率外,在信道估计精度和误码率方面也提供了更好的性能。

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