Zhang Yijia, Liu Ruiying
School of Information Science and Technology, Zhejiang Sci-Tech University, Hangzhou 310018, China.
College of Mechanical and Electrical Engineering, Jiaxing University, Jiaxing 314001, China.
Entropy (Basel). 2020 Feb 17;22(2):223. doi: 10.3390/e22020223.
Since the cloud radio access network (C-RAN) transmits information signals by jointly transmission, the multiple copies of information signals might be eavesdropped on. Therefore, this paper studies the resource allocation algorithm for secure energy optimization in a downlink C-RAN, via jointly designing base station (BS) mode, beamforming and artificial noise (AN) given imperfect channel state information (CSI) of information receivers (IRs) and eavesdrop receivers (ERs). The considered resource allocation design problem is formulated as a nonlinear programming problem of power minimization under the quality of service (QoS) for each IR, the power constraint for each BS, and the physical layer security (PLS) constraints for each ER. To solve this non-trivial problem, we first adopt smooth ℓ 0 -norm approximation and propose a general iterative difference of convex (IDC) algorithm with provable convergence for a difference of convex programming problem. Then, a three-stage algorithm is proposed to solve the original problem, which firstly apply the iterative difference of convex programming with semi-definite relaxation (SDR) technique to provide a roughly (approximately) sparse solution, and then improve the sparsity of the solutions using a deflation based post processing method. The effectiveness of the proposed algorithm is validated with extensive simulations for power minimization in secure downlink C-RANs.
由于云无线接入网络（C-RAN）通过联合传输来发送信息信号，信息信号的多个副本可能会被窃听。因此，本文研究了在下行C-RAN中用于安全能量优化的资源分配算法，通过在信息接收器（IR）和窃听接收器（ER）的信道状态信息（CSI）不完善的情况下，联合设计基站（BS）模式、波束成形和人工噪声（AN）。所考虑的资源分配设计问题被表述为一个非线性规划问题，即在每个IR的服务质量（QoS）、每个BS的功率约束以及每个ER的物理层安全（PLS）约束下的功率最小化问题。为了解决这个具有挑战性的问题，我们首先采用光滑ℓ0范数近似，并针对凸规划问题的差值提出了一种具有可证明收敛性的通用迭代凸差（IDC）算法。然后，提出了一种三阶段算法来解决原始问题，该算法首先应用带有半定松弛（SDR）技术的迭代凸差规划来提供一个大致（近似）稀疏的解，然后使用基于收缩的后处理方法来提高解的稀疏性。通过在安全下行C-RAN中进行广泛的功率最小化仿真，验证了所提算法的有效性。
