Abstract

In this paper, we investigate the secure downlink transmission in a multi-user massive multiple-input multiple-output system assuming there is a passive multi-antenna eavesdropper (Eve) that intends to intercept information of a target user. Specifically, we employ the distributed massive antenna sets at the base station, which are known as remote radio heads (RRHs). With cooperative maximum-ratio transmission beamforming, artificial noise (AN) generation and autonomous power allocation at each RRH, the closed-form deterministic lower bound of the ergodic secrecy rate is derived by random matrix theory. Based on a simplified channel model, the impacts of various parameters on secrecy performance, such as uplink training energy, eavesdropper’s antennas number, power allocation factor, have been analyzed in detail, which provide intuitive insights for optimization and performance evaluation. Moreover, by exploiting complementary geometric programming, an power optimization algorithm over signal and AN power is derived subject to total power and Eve’s signal-to-interference-plus-noise ratio constraints. Numerical results have been presented to reveal the system’s secrecy performance and confirm all analysis results in this paper.

中文翻译：

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多用户分布式大规模MIMO系统中的安全传输和功率分配

摘要

在本文中，我们假设有一个旨在拦截目标用户信息的无源多天线窃听器（Eve），研究了在多用户大规模多输入多输出系统中的安全下行链路传输。具体来说，我们在基站采用了分布式大型天线组，称为远程无线电头（RRH）。通过在每个RRH上协作最大比率传输波束成形，人工噪声（AN）生成和自主功率分配，通过随机矩阵理论推导了遍历保密率的封闭形式确定性下限。基于简化的信道模型，已经详细分析了各种参数对保密性能的影响，例如上行链路训练能量，窃听者的天线数量，功率分配因子，为优化和性能评估提供直观的见解。此外，通过利用互补的几何编程，在总功率和Eve的信噪比加噪声比约束下，得出了信号和AN功率的功率优化算法。本文给出了数值结果，以揭示该系统的保密性能并确认所有分析结果。