This paper considers a Gaussian multi-input multi-output (MIMO) multiple access wiretap (MAC-WT) channel, where an eavesdropper (Eve) wants to extract the confidential information of all users. Assuming that both the legitimate receiver and Eve jointly decode their interested messages, we aim to maximize the sum secrecy rate of the system by precoder design. Although this problem could be solved by first using the iterative majorization minimization (MM) based algorithm to get a sequence of convex log-determinant optimization subproblems and then using some general tools, e.g., the interior point method, to deal with each subproblem, this strategy involves quite high computational complexity. Therefore, we propose a simultaneous diagonalization based low-complexity (SDLC) method to maximize the secrecy rate of a simple one-user wiretap channel, and then use this method to iteratively optimize the covariance matrix of each user. Simulation results show that in contrast to the existing approaches, the SDLC scheme achieves similar secrecy performance but requires much lower complexity.
翻译:本文考虑了高斯多投入多输出(MIMO)多存取窃听器(MAC-WT)多存取窃听器(Eve)希望提取所有用户的机密信息。假设合法接收器和夏娃共同解码他们感兴趣的信息,我们的目标是通过预编码器设计最大限度地实现系统的总保密率。虽然这个问题可以通过首先使用基于迭代主控最小化(MM)的算法来解决,以获得一系列对流对数优化子问题,然后使用一些一般工具,例如内点方法来处理每个子问题,但这一战略涉及相当高的计算复杂性。因此,我们建议采用基于低兼容度的对数化同时法(SDLC)方法,以最大限度地使用简单的单用户窃听器的保密率,然后使用这种方法使每个用户的常态矩阵最优化。模拟结果表明,与现有方法不同的是,SDLC计划实现了相似的保密性,但要求的复杂程度要低得多。