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Joint Information and Jamming Beamforming for Secrecy Rate Maximization in Cognitive Radio Networks

机译:联合信息和干扰波束成形技术在认知无线电网络中的保密率最大化

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In this paper, we consider the secure beamforming design for an underlay cognitive radio multiple-input single-output broadcast channel in the presence of multiple passive eavesdroppers. Our goal is to design a jamming noise (JN) transmit strategy to maximize the secrecy rate of the secondary system. By utilizing the zero-forcing method to eliminate the interference caused by JN to the secondary user, we study the joint optimization of the information and JN beamforming for secrecy rate maximization of the secondary system while satisfying all the interference power constraints at the primary users, as well as the per-antenna power constraint at the secondary transmitter. For an optimal beamforming design, the original problem is a nonconvex program, which can be reformulated as a convex program by applying the rank relaxation method. To this end, we prove that the rank relaxation is tight and propose a barrier interior-point method to solve the resulting saddle point problem based on a duality result. To find the global optimal solution, we transform the considered problem into an unconstrained optimization problem. We then employ Broyden-Fletcher-Goldfarb-Shanno method to solve the resulting unconstrained problem, which helps reduce the complexity significantly, compared with the conventional methods. Simulation results show the fast convergence of the proposed algorithm and substantial performance improvements over the existing approaches.
机译:在本文中,我们考虑了在存在多个无源窃听者的情况下,用于底层认知无线电多输入单输出广播信道的安全波束形成设计。我们的目标是设计一种干扰噪声(JN)传输策略,以最大程度地提高次级系统的保密率。通过利用零强迫方法消除JN对次级用户的干扰,我们研究了信息和JN波束成形的联合优化,以在满足主要用户的所有干扰功率约束的情况下最大化次级系统的保密率,以及辅助发射机处的每天线功率限制。对于最佳波束成形设计,最初的问题是非凸程序,可以通过应用秩松弛法将其重新构造为凸程序。为此,我们证明了秩松弛是紧密的,并提出了一种基于对偶结果的屏障内点方法来解决由此产生的鞍点问题。为了找到全局最优解,我们将考虑的问题转换为无约束的优化问题。然后,我们采用Broyden-Fletcher-Goldfarb-Shanno方法来解决由此产生的无约束问题,与传统方法相比,这有助于显着降低复杂性。仿真结果表明,该算法具有较快的收敛速度,并且相对于现有方法具有明显的性能提升。

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