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An Efficient Approximation for Nakagami-m Quantile Function Based on Generalized Opposition-Based Quantum Salp Swarm Algorithm

机译：基于广义对立基于广义的Quantum Salp群算法的Nakagami-M分位数函数的有效近似

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摘要

With the further research in communication systems, especially in wireless communication systems, a statistical model called Nakagami-m distribution appears to have better performance than other distributions, including Rice and Rayleigh, in explaining received faded envelopes. Therefore, the Nakagami-m quantile function plays an important role in numerical calculations and theoretical analyses for wireless communication systems. However, it is quite difficult to operate numerical calculations and theoretical analyses because Nakagami-m quantile function has no exact closed-form expression. In order to obtain the closed-form expression that is able to fit the curve of Nakagami-m quantile function as well as possible, we adopt the method of curve fitting in this paper. An efficient expression for approximating the Nakagami-m quantile function is proposed first and then a novel heuristic optimization algorithm-generalized opposition-based quantum salp swarm algorithm (GO-QSSA)-which contains quantum computation, intelligence inspired by salp swarm and generalized opposition-based learning strategy in quantum space, to compute the coefficients of the proposed expression. Meanwhile, we compare GO-QSSA with three swarm intelligence algorithms: artificial bee colony algorithm (ABC), particle swarm optimization algorithm (PSO), and salp swarm algorithm (SSA). The comparing simulation results reveal that GO-QSSA owns faster convergence speed than PSO, ABC, and SSA. Moreover, GO-QSSA is capable of computing more accurately than traditional algorithms. In addition, the simulation results show that compared with existing curve-fitting-based methods, the proposed expression decreases the fitting error by roughly one order of magnitude in most cases and even higher in some cases. Our approximation is proved to be simple and efficient.
机译：通过进一步研究通信系统，特别是在无线通信系统中，据解释接收的褪色信封，似乎具有比其他分布的更好的性能，似乎具有比其他分布更好的性能。因此，Nakagami-M分位数函数在无线通信系统的数值计算和理论分析中起着重要作用。然而，操作数值计算和理论分析是非常困难的，因为Nakagami-M分位数函数没有完全闭合形式的表达。为了获得能够符合Nakagami-M分位数功能的曲线的闭合形式表达，我们采用本文采用曲线配件的方法。首先提出了近似Nakagami-M分位数函数的有效表达，然后是一种新型启发式优化算法 - 广泛的基于对立的对立的Quantum Salp群算法（Go-QSSA） - 包含量子计算，受到SALP群和广义反对的智力启发 - 基于量子空间的基于学习策略，计算所提出的表达的系数。同时，我们将Go-QSSA与三种群智能算法进行比较：人造蜂菌落算法（ABC），粒子群优化算法（PSO）和SALP群算法（SSA）。比较仿真结果表明，Go-QSSA拥有比PSO，ABC和SSA更快的收敛速度。此外，Go-QSSA能够比传统算法更准确地计算。另外，仿真结果表明，与现有的基于曲线拟合的方法相比，所提出的表达在大多数情况下，在大多数情况下，在大多数情况下，在大多数情况下甚至更高，将拟合误差降低大约一个级。我们的近似被证明是简单而有效的。

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  • 来源
    《Mathematical Problems in Engineering》 |2019年第17期|8291063.1-8291063.13|共13页
  • 作者

    Gao Hongyuan; Hou Yangyang; Zhang Shibo; Diao Ming;

  • 作者单位

    Harbin Engn Univ Coll Informat & Commun Engn 145 Nantong St Harbin 150001 Heilongjiang Peoples R China;

    Harbin Engn Univ Coll Informat & Commun Engn 145 Nantong St Harbin 150001 Heilongjiang Peoples R China;

    Harbin Engn Univ Coll Informat & Commun Engn 145 Nantong St Harbin 150001 Heilongjiang Peoples R China;

    Harbin Engn Univ Coll Informat & Commun Engn 145 Nantong St Harbin 150001 Heilongjiang Peoples R China;

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