基于AMC的ofdma无线蜂窝系统连接级接入等待时间分布的近似计算

Ruben P. Murillo-Perez, C. B. Rodríguez-Estrello, F. A. Cruz-Pérez
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引用次数: 0

摘要

本文提出了基于ofdma的有限缓冲无线蜂窝系统在先到先得(FCFS)原则和自适应调制与编码(AMC)原则下,近似计算接入(连接级)等待时间分布的两种解析方法。在前人的研究中已经证明,访问等待时间是具有相同分布但随机均值的随机变量的随机和。因此,对访问等待时间概率分布进行数值评估的计算复杂度随着缓冲区的大小和覆盖区域的数量呈指数增长。为了降低计算复杂度,提出了在一定交通负荷条件下,利用负指数分布来近似整个通道等待时间分布。并利用利特尔定理给出了一种计算其参数的有效方法。更一般的方法是基于中心极限定理(CLT)。特别地,它认为在给定位置排队的服务请求的条件访问等待时间可以用高斯分布充分近似。提出的近似方法进行了数值评估,并与精确的数学分析进行了比较,以累积分布函数的形式。数值结果表明,在一定条件下,两种近似的CDFs与精确分析的最大百分比误差小于10%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Approximated Calculations of Connection Level Access Waiting Time Distribution in OFDMA-Based Wireless Cellular Systems with AMC
In this paper, two analytical approaches to approximately calculate the access (at connection level) waiting time distribution for an OFDMA-based wireless cellular system with finite buffering under First-Come, First-Served (FCFS) discipline and Adaptive Modulation and Coding (AMC) are proposed. It has been demonstrated in previous published works that access waiting time is a random sum of random variables with the same distribution but random mean. Therefore, the computational complexity for the numerical evaluation of the access waiting time probability distribution increases exponentially with the size of the buffer and the number of coverage regions. In order to reduce the computational complexity, the use of negative exponential distribution is proposed to approximate the whole access waiting time distribution for certain conditions of traffic load. Moreover, an efficient way to calculate its parameter through the Little's theorem is proposed. A more general approach is based on the central limit theorem (CLT). In particular, it considers that the conditional access waiting time of a service request queued in the a given position can be adequately approximated by a Gaussian distribution. The proposed approximation approaches are numerically evaluated and compared against the exact mathematical analysis in terms of the cumulative distribution function. Numerical results show that the maximum percentage error between the both approximated CDFs is smaller than 10% relative to the exact analysis under certain conditions.
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