Physical layer security (PLS) is an emerging area for information security against eavesdroppers (Eve). Information security of any system can also be improved by using friendly jammers that produce interference signals to Eve. Traditional security techniques are limited by the processing power of the wireless nodes, whereas PLS can achieve communication secrecy without requiring computationally expensive cryptographic operations. The relay networks have emerged as a promising technology to enhance the performance of the wireless systems. This paper proposes a joint resource optimization framework for the PLS of dual-hop decode and forward (DF) relay network with and without cooperative jamming. In particular, the proposed framework consists of a base station (BS), multiple users, DF relays, multiple subcarriers, and an Eve. Our objective is to maximize the sum secrecy rate (SR) through optimal power loading over different subcarriers at BS and relay nodes, and efficient subcarrier assignment. We formulate a mixed binary integer programing problem for secrecy optimization and adopt Lagrangian dual method to achieve the efficient solutions. We also provide three benchmark frameworks, i.e., joint power optimization with random subcarrier assignment, equal power allocation with efficient subcarrier assignment and equal power with random subcarrier assignment to guage the performance of our joint resource optimization framework. Simulation results unveil that the proposed joint resource optimization framework under cooperative jamming and without jamming performs significantly better than the benchmark frameworks.

中文翻译：

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双跳多载波解码和转发中继网络物理层安全的资源优化框架


物理层安全（PLS）是针对窃听者（Eve）的信息安全的新兴领域。任何系统的信息安全都可以通过使用对 Eve 产生干扰信号的友好干扰器来提高。传统的安全技术受到无线节点处理能力的限制，而 PLS 可以实现通信保密，而不需要计算量大的加密操作。中继网络已成为增强无线系统性能的一项有前途的技术。本文提出了一种针对有和没有协作干扰的双跳解码和转发（DF）中继网络的 PLS 的联合资源优化框架。特别是，所提出的框架由基站（BS）、多个用户、DF中继、多个子载波和Eve组成。我们的目标是通过基站和中继节点不同子载波上的最佳功率负载以及有效的子载波分配来最大化总保密率（SR）。我们制定了一个用于保密优化的混合二进制整数规划问题，并采用拉格朗日对偶方法来实现有效的解决方案。我们还提供了三个基准框架，即随机子载波分配的联合功率优化、高效子载波分配的等功率分配和随机子载波分配的等功率来衡量我们的联合资源优化框架的性能。仿真结果表明，所提出的联合资源优化框架在协作干扰和无干扰下的性能明显优于基准框架。