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A Low Complexity Subspace-Based Blind Channel Estimation For MIMO-OFDM

机译:用于MIMO-OFDM的基于低复杂性子空间的盲信道估计

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The current subspace-based blind channel estimation for MIMO-OFDM system has the problems of high complexity due to matrix decomposition. In this paper, we proposed an improved subspace-based channel estimation algorithm, which is based on the method of the permutations and combinations on the transceiver signal. To reduce the complexity of singular value decomposition, this article put forward the idea of iterative instead. Theoretical analysis and simulation results showed that this algorithm could decrease the complexity compared with the traditional subspace algorithms in ensuring the accuracy and the converge.
机译:用于MIMO-OFDM系统的基于子空间的盲信道估计具有由于矩阵分解引起的高复杂性问题。在本文中,我们提出了一种改进的基于子空间的信道估计算法,其基于对收发器信号的排列和组合的方法。为了降低奇异值分解的复杂性,本文提出了迭代的想法。理论分析和仿真结果表明,与传统的子空间算法相比,该算法可以降低复杂性,确保精度和收敛。

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