Linear Precoding for Finite-Alphabet Inputs Over MIMO Fading Channels With Statistical CSI
Linear Precoding for Finite-Alphabet Inputs Over MIMO Fading Channels With Statistical CSI
复制标题
DOI：
10.1109/tsp.2012.2188717
复制
发表时间：
2012-06
影响因子：
5.4
通讯作者：
Weiliang Zeng;C. Xiao;Mingxi Wang;Jianhua Lu
中科院分区：
文献类型：
--
作者：
Weiliang Zeng;C. Xiao;Mingxi Wang;Jianhua Lu
本文研究了在发送端已知统计信道状态信息的情况下，最大化多输入多输出衰落信道平均互信息的线性预编码器设计。它从有限字母输入的角度阐述了设计，这导致了一个在实践中非常重要但在理论上极其困难的问题：第一，平均互信息缺乏闭合形式的表达，涉及到令人望而却步的计算负担。其次，预编码器的优化是非凹的，容易陷入局部极大值。为了解决这些问题，本研究首先推导了平均互信息的上下界，与直接计算平均互信息相比，计算复杂度降低了几个数量级。它证明了最大化上下界是渐近最优的，并且表明，在移动不变的情况下，下界实际上为各种衰落信道的平均互信息提供了非常精确的近似。本文进一步提出了利用下界作为一种低复杂度和精确的替代方案来开发一种两步算法来寻找一个接近全局最优的预编码器。数值算例验证了该算法的收敛和有效性。与传统的预编码方法相比，所提出的线性预编码方法比现有的预编码算法具有显著的性能提升。当MIMO信道的空间相关性增加时，增益变得更加可观。
This paper investigates the linear precoder design that maximizes the average mutual information of multiple-input multiple-output fading channels with statistical channel state information known at the transmitter. It formulates the design from the standpoint of finite-alphabet inputs, which leads to a problem that is very important in practice but extremely difficult in theory: First, the average mutual information lacks closed-form expression and involves prohibitive computational burden. Second, the optimization over the precoder is nonconcave and thus easily gets stuck in local maxima. To address these issues, this study first derives lower and upper bounds for the average mutual information, in which the computational complexity is reduced by several orders of magnitude compared to calculating the average mutual information directly. It proves that maximizing the bounds is asymptotically optimal and shows that, with a constant shift, the lower bound actually offers a very accurate approximation to the average mutual information for various fading channels. This paper further proposes utilizing the lower bound as a low-complexity and accurate alternative for developing a two-step algorithm to find a near global optimal precoder. Numerical examples demonstrate the convergence and efficacy of the proposed algorithm. Compared to its conventional counterparts, the proposed linear precoding method provides significant performance gain over existing precoding algorithms. The gain becomes more substantial when the spatial correlation of MIMO channels increases.