具有特征模划分的渐近MIMO人工噪声保密率

A. D. Harper, R. Baxley
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引用次数: 0

摘要

在多输入多输出(MIMO)窃听信道系统中,可以在主信道的零空间中传输人工噪声以保证接收端的保密性。先前的MIMO渐近容量公式假设将利用所有信道特征模。然而,优化可能的天线配置需要划分可用的特征模式。通常情况下,当信号传输仅使用某些特征模态时,很难找到精确的闭型渐近解。我们提出了一个具有特征模式划分的大规模MIMO近似,对实际天线数量准确,并且大大降低了计算复杂度。
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Asymptotic MIMO artificial-noise secrecy rates with eigenmode partitioning
In a multiple-input multiple-output (MIMO) wiretap channel system, it has been shown that artificial noise can be transmitted in the null space of the main channel to guarantee the secrecy at the intended receiver. Previous formulas for MIMO asymptotic capacity assume that all channel eigenmodes will be utilized. However, optimizing over possible antenna configurations requires partitioning the available eigenmodes. With only some eigenmodes used for signal transmission, finding an exact closed-form asymptotic solution is, in general, intractable. We present a large-scale MIMO approximation with eigenmode partitioning, accurate for realistic numbers of antennas, and with greatly reduced computational complexity.
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