Jiang Bin, Qu Linbo, Huang Yufei, Zheng Yifei, You Li, Wang Wenjin
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China.
Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space, Ministry of Industry and Information Technology, Ministry of Industry and Information Technology, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
Entropy (Basel). 2020 Oct 12;22(10):1145. doi: 10.3390/e22101145.
Herein, we focus on energy efficiency optimization for massive multiple-input multiple-output (MIMO) downlink secure multicast transmission exploiting statistical channel state information (CSI). Privacy engineering in the field of communication is a hot issue under study. The common signal transmitted by the base station is multicast transmitted to multiple legitimate user terminals in our system, but an eavesdropper might eavesdrop this signal. To achieve the energy efficiency utility-privacy trade-off of multicast transmission, we set up the problem of maximizing the energy efficiency which is defined as the ratio of the secure transmit rate to the power consumption. To simplify the formulated nonconvex problem, we use a lower bound of the secure multicast rate as the molecule of the design objective. We then obtain the eigenvector of the optimal transmit covariance matrix into a closed-form, simplifying the matrix-valued multicast transmission strategy problem into a power allocation problem in the beam domain. By utilizing the Minorize-Maximize method, an iterative algorithm is proposed to decompose the secure energy efficiency optimization problem into a sequence of iterative fractional programming subproblems. By using Dinkelbach's transform, each subproblem becomes an iterative problem with the concave objective function, and it can be solved by classical convex optimization. We guarantee the convergence of the two-level iterative algorithm that we propose. Besides, we reduce the computational complexity of the algorithm by substituting the design objective with its deterministic equivalent. The numerical results show that the approach we propose performs well compared with the conventional methods.
在此，我们专注于利用统计信道状态信息（CSI）对大规模多输入多输出（MIMO）下行链路安全多播传输进行能效优化。通信领域的隐私工程是一个正在研究的热点问题。在我们的系统中，基站发送的公共信号被多播传输到多个合法用户终端，但窃听者可能会窃听该信号。为了实现多播传输的能效效用 - 隐私权衡，我们建立了一个将能效最大化的问题，该能效被定义为安全传输速率与功耗之比。为了简化所制定的非凸问题，我们使用安全多播速率的下限作为设计目标的分子。然后，我们以封闭形式得到最优发射协方差矩阵的特征向量，将矩阵值多播传输策略问题简化为波束域中的功率分配问题。通过利用最小化 - 最大化方法，提出了一种迭代算法，将安全能效优化问题分解为一系列迭代分数规划子问题。通过使用丁克尔巴赫变换，每个子问题都变成了一个具有凹目标函数的迭代问题，可以通过经典凸优化来求解。我们保证了所提出的两级迭代算法的收敛性。此外，我们通过用其确定性等价物替换设计目标来降低算法的计算复杂度。数值结果表明，我们提出的方法与传统方法相比表现良好。
