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arXiv 2311.08804cs.ITeess.SPmath.IT
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混合高斯-冲击噪声下信道容量界限与低复杂度星座塑形

Capacity Bounds and Low-Complexity Constellation Shaping under Mixed Gaussian-Impulsive Noise

Tianfu Qi, Jun Wang

AI总结:

本文提出了一种在混合高斯-冲击噪声环境下,通过熵功率不等式推导信道容量界限,并设计低复杂度星座塑形方法,实现高互信息传输。

摘要:

本文研究了在无记忆混合噪声下的信道容量界限和星座塑形界限,该噪声由冲击噪声(IN)和白高斯噪声(WGN)组成。通过熵功率不等式和容量的双重表达式推导出容量界限。证明所提出的下界和上界渐近收敛于真实信道容量,并获得了解析的渐近容量表达式。利用这一性质,我们设计了一种无需迭代过程的低复杂度星座塑形方法。仿真结果表明,推导出的界限非常紧,塑形后的星座在所有考虑的基线方案中实现了最高的互信息。

英文摘要:

This paper investigates the bounds on channel capacity and constellation shaping under memoryless mixed noise, which is composed of impulsive noise (IN) and white Gaussian noise (WGN). The capacity bounds are derived using the entropy power inequality and the dual expression of capacity. It is then shown that the proposed lower and upper bounds asymptotically converge to the true channel capacity, and the analytic asymptotic capacity expression is obtained. Leveraging this property, we design a low-complexity constellation shaping method that operates without iterative procedures. Simulation results demonstrate that the derived bounds are remarkably tight, and the shaped constellation achieves the highest mutual information among all considered baseline schemes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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