| 张广大,任清华,樊志凯.基于人工神经网络的联合中继和干扰选择策略研究[J].电子测量与仪器学报,2021,35(7):20-29 |
| 基于人工神经网络的联合中继和干扰选择策略研究 |
| Research on joint relay and jammer selection strategybased on artificial neural network |
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| DOI： |
| 中文关键词: 物理层安全 中继选择 人工神经网络 协作干扰 安全中断概率 信道状态信息 |
| 英文关键词:physical layer security relay selection artificial neural network cooperative interference secrecy outage probability channel state information |
| 基金项目:国家重点实验室合作基金（kx162600022）项目资助 |
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| 摘要点击次数: 487 |
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| 中文摘要: |
| 针对多中继通信网络,中继选择算法效率低及潜在窃听节点的安全威胁问题。 提出一种基于人工神经网络的联合中继
和干扰节点选择策略。 首先,采用解码转发(decode-and-forward,DF)中继协议,构建存在窃听节点的多中继协作通信网络,结合
协作干扰策略,推导得到系统安全中断概率的闭合表达式;然后,对神经网络进行训练,将相关节点的信道状态信息( channel
state information,CSI)作为输入对模型进行训练,获得最优模型参数;最后,利用部分数据集验证模型,仿真结果表明对最优节点
选择的正确率能够达到 93%以上。 与传统选择方案相比,所提方案实现复杂度降低且计算时间明显减少,并且有效改善了系统
的安全性能。 |
| 英文摘要: |
| Aiming at the problems of low efficiency of relay selection algorithm and security threat of potential eavesdropping nodes in
multi-relay communication network. A joint relay and jammer selection strategy based on artificial neural network is proposed. Firstly,
the decode-and-forward ( DF ) relay protocol is adopted to construct the multi-relay cooperative communication network with
eavesdropper, and the closed form expression of the security outage probability is derived by combination with the cooperative jamming
strategy. Then, the neural network is trained, and the channel state information (CSI) of the relevant nodes is taken as the input data to
train the model to obtain the optimal model parameters. Finally, some data sets are used to verify the model, and the simulation results
show that the accuracy of optimal nodes selection can reach more than 93%. Compared with the traditional selection scheme based on
exhaustive search and support vector machine, the proposed scheme reduces the implementation complexity and computation time
significantly, and effectively improve the security performance of the system. |
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