当前位置: X-MOL 学术IEEE Trans. Commun. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Secure Communication for Spatially Sparse Millimeter-Wave Massive MIMO Channels via Hybrid Precoding
IEEE Transactions on Communications ( IF 7.2 ) Pub Date : 2020-02-01 , DOI: 10.1109/tcomm.2019.2954517
Jindan Xu , Wei Xu , Derrick Wing Kwan Ng , A. Lee Swindlehurst

In this paper, we investigate secure communication over sparse millimeter-wave (mm-Wave) massive multiple-input multiple-output (MIMO) channels by exploiting the spatial sparsity of legitimate user’s channel. We propose a secure communication scheme in which information data is precoded onto dominant angle components of the sparse channel through a limited number of radio-frequency (RF) chains, while artificial noise (AN) is broadcast over the remaining nondominant angles interfering only with the eavesdropper with a high probability. It is shown that the channel sparsity plays a fundamental role analogous to secret keys in achieving secure communication. Hence, by defining two statistical measures of the channel sparsity, we analytically characterize its impact on secrecy rate. In particular, a substantial improvement on secrecy rate can be obtained by the proposed scheme due to the uncertainty, i.e., “entropy”, introduced by the channel sparsity which is unknown to the eavesdropper. It is revealed that sparsity in the power domain can always contribute to the secrecy rate. In contrast, in the angle domain, there exists an optimal level of sparsity that maximizes the secrecy rate. The effectiveness of the proposed scheme and derived results are verified by numerical simulations.

中文翻译:

通过混合预编码实现空间稀疏毫米波大规模 MIMO 信道的安全通信

在本文中,我们通过利用合法用户信道的空间稀疏性来研究稀疏毫米波 (mm-Wave) 大规模多输入多输出 (MIMO) 信道上的安全通信。我们提出了一种安全通信方案,其中信息数据通过有限数量的射频 (RF) 链预编码到稀疏信道的主角分量上,而人工噪声 (AN) 在其余的非主角上广播,仅干扰窃听者的概率很高。结果表明,信道稀疏性在实现安全通信方面起着类似于密钥的基本作用。因此,通过定义信道稀疏性的两个统计量度,我们分析表征了其对保密率的影响。特别是,由于窃听者未知的信道稀疏性引入的不确定性,即“熵”,所提出的方案可以获得对保密率的实质性改进。结果表明,功率域中的稀疏性总是对保密率有贡献。相比之下,在角度域中,存在最大化保密率的最佳稀疏水平。通过数值模拟验证了所提出的方案和导出结果的有效性。
更新日期:2020-02-01
down
wechat
bug