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Polynomial matrix decompositions and semi-blind channel estimation for MIMO frequency-selective channels

机译:MIMO选频信道的多项式矩阵分解和半盲信道估计

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The authors propose a semi-blind channel estimation (semi-BCE) and precoding/decoding technique for frequency selective (FS) multiple-input multiple-output (MIMO) channels. A FS MIMO channel can be represented using a matrix whose elements are polynomials; hence their method is based on polynomial matrix decomposition. Polynomial eigenvalue decomposition (PEVD) and polynomial QR decomposition (PQRD) are the generalisation of eigenvalue decomposition and QR decomposition; they are suitable for decoupling and precoding of FS MIMO channels. As the coding of communication channels requires reliable estimation of the channel, a semi-BCE scheme, coupled with PQRD/PEVD-based MIMO-channel decomposition, is attractive since this reduces training overhead (pilot transmission) considerably, resulting in higher spectral efficiency. The proposed semi-BCE algorithm is a generalisation of a recently developed single-input single output BCE method to MIMO systems. A new class of PQRD algorithms is introduced, which is based on the recently-developed sequential matrix diagonalisation (SMD). The decoders produced by the proposed SMD-based PQRD algorithm are shown to be more suitable (efficient) for MIMO-channel equalisation than those generated by the prior art. Computer simulations show that the proposed MIMO-channel coding strategy compares favourably to state-of-the-art MIMO systems, in terms of bit error rate performance, while reducing the overhead.
机译:作者提出了一种用于频率选择(FS)多输入多输出(MIMO)信道的半盲信道估计(semi-BCE)和预编码/解码技术。可以使用元素为多项式的矩阵表示FS MIMO信道。因此,他们的方法基于多项式矩阵分解。多项式特征值分解(PEVD)和多项式QR分解(PQRD)是特征值分解和QR分解的概括;它们适用于FS MIMO信道的解耦和预编码。由于通信信道的编码需要对信道进行可靠的估计,因此,将半BCE方案与基于PQRD / PEVD的MIMO信道分解相结合是有吸引力的,因为这会大大减少训练开销(导频传输),从而提高频谱效率。提出的半BCE算法是对MIMO系统最近开发的单输入单输出BCE方法的概括。引入了一种新的PQRD算法,它基于最近开发的顺序矩阵对角化(SMD)。由所提出的基于SMD的PQRD算法产生的解码器显示出比现有技术所产生的解码器更适合(有效)用于MIMO信道均衡。计算机仿真表明,就误码率性能而言,所提出的MIMO信道编码策略与最新的MIMO系统相比具有优势,同时降低了开销。

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