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Iterative Precoder Design and User Scheduling for Block-Diagonalized Systems

机译:块对角化系统的迭代预编码器设计和用户调度

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摘要

The block diagonalization (BD) scheme is a low-complexity suboptimal precoding technique for multiuser multiple input-multiple output (MIMO) downlink channels, which completely precancels the multiuser interference. Accordingly, the precoder of each user lies in the null space of other users' channel matrices. In this paper, we propose an iterative algorithm using QR decompositions (QRDs) to compute the precoders. Specifically, to avoid dealing with a large concatenated matrix, we apply the QRD to a sequence of matrices of lower dimensions. One problem of BD schemes is that the number of users that can be simultaneously supported is limited due to zero interference constraints. When the number of users is large, a set of users must be selected, and selection algorithms should be designed to exploit the multiuser diversity gain. Finding the optimal set of users requires an exhaustive search, which has too high computational complexity to be practically useful. Based on the iterative precoder design, this paper proposes a low-complexity user selection algorithm using a greedy method, in which the precoders of selected users are recursively updated after each selection step. The selection metric of the proposed scheduling algorithm relies on the product of the squared row norms of the effective channel matrices, which is related to the eigenvalues by the Hadamard and Schur inequalities. An asymptotic analysis is provided to show that the proposed algorithm can achieve the optimal sum rate scaling of the MIMO broadcast channel. The numerical results show that the proposed algorithm achieves a good trade-off between sum rate performance and computational complexity. When users suffer different channel conditions, providing fairness among users is of critical importance. To address this problem, we also propose two fair scheduling (FS) algorithms, one imposing fairness in the approximation of the data rate, and another directly imposing fairness in the product of the sq- ared row norms of the effective channel matrices.
机译:块对角化(BD)方案是一种用于多用户多输入多输出(MIMO)下行链路信道的低复杂度次优预编码技术,可完全消除多用户干扰。因此,每个用户的预编码器位于其他用户的信道矩阵的空空间中。在本文中,我们提出了一种使用QR分解(QRD)的迭代算法来计算预编码器。具体而言,为避免处理较大的级联矩阵,我们将QRD应用于一系列较低维度的矩阵。 BD方案的一个问题是,由于零干扰约束,可以同时支持的用户数量受到限制。当用户数量很大时,必须选择一组用户,并且应该设计选择算法以利用多用户分集增益。找到最佳的用户集合需要详尽的搜索,该搜索的计算复杂度过高,无法实际使用。在迭代预编码器设计的基础上,提出了一种采用贪婪算法的低复杂度用户选择算法,该算法在每个选择步骤后递归更新所选用户的预编码器。所提出的调度算法的选择度量依赖于有效信道矩阵的平方行范数的乘积,该乘积与Hadamard和Schur不等式的特征值有关。通过渐近分析表明,该算法可以实现MIMO广播信道的最优总速率缩放。数值结果表明,该算法在求和速率性能和计算复杂度之间取得了良好的折衷。当用户遭受不同的信道条件时,在用户之间提供公平至关重要。为了解决这个问题,我们还提出了两种公平调度(FS)算法,一种是在数据速率近似中施加公平性,另一种是在有效通道矩阵的平方行范数乘积中直接施加公平性。

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