Performance Evaluation of a Cognitive Radio Network with Exponential and Truncated Usage Models

Waqas Ahmed, Jason H. Gao, M. Faulkner
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引用次数: 26

Abstract

In this paper, we study the forced termination probability, blocking probability and throughput of secondary users with practical usage models, which include fixed, truncated exponential, truncated lognormal, truncated Pareto distributions. Moreover, we compare the results of these usage models with the well known exponential distribution model. We consider two system scenarios with/without spectrum handoff. For all distributions, introduction of spectrum handoff provides significant gains in forced termination probability and throughput. We found that the behaviour of all the truncated distributions is similar to exponential distribution. The results show that among all the distributions models, the secondary user connections with fixed length has the largest aggregate throughput, whereas the truncated Pareto has the smallest aggregate throughput. In general, as the mean duration of secondary user connections decreases, the throughput increases.
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基于指数和截断使用模型的认知无线网络性能评估
本文利用固定分布、截断指数分布、截断对数正态分布、截断帕累托分布等实际使用模型,研究了二次用户的强制终止概率、阻塞概率和吞吐量。此外,我们将这些使用模型的结果与众所周知的指数分布模型进行了比较。我们考虑两种有/没有频谱切换的系统场景。对于所有分布,频谱切换的引入在强制终止概率和吞吐量方面提供了显著的增益。我们发现所有截断分布的行为都与指数分布相似。结果表明:在所有分布模型中,固定长度的次要用户连接具有最大的总吞吐量,而截断的Pareto具有最小的总吞吐量。通常,随着辅助用户连接的平均持续时间的减少,吞吐量会增加。
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