Transmit Solutions for MIMO Wiretap Channels using Alternating Optimization
Transmit Solutions for MIMO Wiretap Channels using Alternating Optimization
复制标题
DOI：
10.1109/jsac.2013.130906
复制
发表时间：
2013-09-01
影响因子：
16.4
通讯作者：
Luo, Zhi-Quan
中科院分区：
文献类型：
--
作者：
Li, Qiang;Hong, Mingyi;Luo, Zhi-Quan
本文考虑了多输入多输出（MIMO）窃听通道中的传输优化，其中我们旨在最大程度地提高MIMO通道的保密能力或速率，这是一个或多个窃听者的偷听。此类优化问题是非凸的，并且似乎很困难，尤其是在多欧文dropper方案中。在本文中，我们提出了一种交替优化（AO）方法来解决这些保密优化问题。我们首先考虑单个窃听器场景中的保密能力最大化（SCM）问题。 AO算法是通过明智的SCM重新制定得出的。该算法以交替的方式进行了某种重新加权和填充水，因此在计算上可以有效地实施。我们还证明，AO算法可以保证将SCM问题的Karush-Kuhn-Tucker（KKT）点收敛。然后，我们将注意力转移到多个窃听的情况下，其中考虑了人造噪声（AN）的保密速率最大化（SRM）问题。尽管AN-ADED SRM问题的问题结构比以前的SCM更复杂，但我们表明AO可以扩展到与前者打交道，其中通过以交替的方式解决凸问题来解决该问题。同样，结果被证明具有KKT点收敛保证。为了进行快速实施，还得出了基于平滑和投影梯度的自定义设计的AO算法。模拟证明了所提出的算法的保密率性能和计算效率。
This paper considers transmit optimization in multi-input multi-output (MIMO) wiretap channels, wherein we aim at maximizing the secrecy capacity or rate of an MIMO channel overheard by one or multiple eavesdroppers. Such optimization problems are nonconvex, and appear to be difficult especially in the multi-eavesdropper scenario. In this paper, we propose an alternating optimization (AO) approach to tackle these secrecy optimization problems. We first consider the secrecy capacity maximization (SCM) problem in the single eavesdropper scenario. An AO algorithm is derived through a judicious SCM reformulation. The algorithm conducts some kind of reweighting and water-filling in an alternating fashion, and thus is computationally efficient to implement. We also prove that the AO algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT) point of the SCM problem. Then, we turn our attention to the multiple eavesdropper scenario, where the artificial noise (AN)-aided secrecy rate maximization (SRM) problem is considered. Although the AN-aided SRM problem has a more complex problem structure than the previous SCM, we show that AO can be extended to deal with the former, wherein the problem is handled by solving convex problems in an alternating fashion. Again, the resulting AO method is proven to have KKT point convergence guarantee. For fast implementation, a custom-designed AO algorithm based on smoothing and projected gradient is also derived. The secrecy rate performance and computational efficiency of the proposed algorithms are demonstrated by simulations.