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McLeish Distribution: Performance of Digital Communications Over Additive White McLeish Noise (AWMN) Channels

机译:McLeish分布:数字通信对添加性白色MCLEISH噪声(AWMN)通道的性能

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The objective of this article is to propose and statistically validate a more general additive non-Gaussian noise distribution, which we term McLeish distribution, whose random nature can model different impulsive noise environments commonly encountered in practice and provides a robust alternative to Gaussian noise distribution. In particular, for the first time in the literature, we establish the laws of McLeish distribution and therefrom derive the laws of the sum of McLeish distributions by obtaining closed-form expressions for their probability density function (PDF), cumulative distribution function (CDF), complementary CDF ((CDF)-D-2), moment-generating function (MGF) and higher-order moments. Further, for certain problems related to the envelope of complex random signals, we extend McLeish distribution to complex McLeish distribution and thereby propose circularly/elliptically symmetric (CS/ES) complex McLeish distributions with closed-form PDF, CDF, MGF and higher-order moments. For generalization of one-dimensional distribution to multi-dimensional distribution, we develop and propose both multivariate McLeish distribution and multivariate complex CS/ES (CCS/CES) McLeish distribution with analytically tractable and closed-form PDF, CDF, (CDF)-D-2 and MGF. In addition to the proposed McLeish distribution framework and for its practical illustration, we theoretically investigate and prove the existence of McLeish distribution as additive noise in communication systems. Accordingly, we introduce additive white McLeish noise (AWMN) channels. For coherenton-coherent signaling over AWMN channels, we propose novel expressions for maximum a priori (MAP) and maximum likelihood (ML) symbol decisions and thereby obtain closed-form expressions for both bit error rate (BER) of binary modulation schemes and symbol error rate (SER) of various M-ary modulation schemes. Further, we verify the validity and accuracy of our novel BER/SER expressions with some selected numerical examples and some computer-based simulations.
机译:本文的目的是提出和统计验证更一般的添加剂非高斯噪声分布​​,我们术语逐步分布,其随机性质可以模拟在实践中通常遇到的不同冲动噪声环境,并提供高斯噪声分布​​的稳健替代方案。特别是,在文献中首次,我们通过获得概率密度函数(PDF),累积分布函数(CDF)来建立MCLeish分布规律,从而通过获得闭合形式的表达式,从而通过获得闭合形式的表达式来衍生MCLeish分布的规律。 ,互补的CDF((CDF)-D-2),时刻生成函数(MGF)和高阶矩。此外,对于与复杂随机信号的包络相关的某些问题,我们将Mcleish分布延伸到复杂的迁移分布,从而提出圆形/椭圆对称(CS / ES)复杂的循环分布,具有闭合形式PDF,CDF,MGF和高阶时刻。为了向多维分布的一维分布概括,我们用分析易动和闭合的PDF,CDF,(CDF)-D,开发和提出多变量的MCLeish分布和多元综合CS / ES(CCS / CES)MCLeish分布。 -2和mgf。除了拟议的MCLeish分配框架和其实际插图外,我们理论上还研究并证明了MCLeish分布作为通信系统中的添加噪声的存在。因此,我们引入了添加剂白色Mcleish噪声(AWMN)通道。对于AWMN通道的相干/非相干信令,我们提出了最大值<斜体>的新表达式(MAP)和最大似然(ML)符号决策,从而获得误码率的闭合表达式(各种M-ARY调制方案的二进制调制方案和符号错误率(SER)的BER。此外,我们验证了我们的小说BER / SER表达式的有效性和准确性,以及一些选定的数值示​​例和一些基于计算机的模拟。

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