Robust spectrum allocation for cognitive radio networks

G. Capdehourat, Federico Larroca, P. Belzarena
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Abstract

In recent years we have seen the success of wireless communications in unlicensed frequency bands, mainly driven by the 802.11 standard. The clear trend in the growth of traffic demand suggests that spectrum scarcity will be a serious threat to reach the capacity needs in the near future. Looking for more available spectrum, regulators have already begun to study secondary assignments in licensed bands, based on the recent cognitive network paradigm. In this context, we focus our work in the analysis of optimum spectrum allocation mechanisms. We introduce a stochastic model to formulate the problem, considering primary users' activity and a periodically scheduled assignment scheme. To solve the problem we propose a novel robust solution, which we argue is superior to an expectation based approach, comparing both alternatives through extensive simulations.
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认知无线电网络的鲁棒频谱分配
近年来,在802.11标准的推动下,无线通信在免授权频带上取得了成功。流量需求增长的明显趋势表明,频谱短缺将在不久的将来成为满足容量需求的严重威胁。为了寻找更多可用的频谱,监管机构已经开始研究基于最近认知网络范式的许可频段的二次分配。在此背景下,我们的工作重点是分析最佳频谱分配机制。我们引入了一个随机模型来描述这个问题,考虑了主要用户的活动和一个定期调度的分配方案。为了解决这个问题,我们提出了一种新的鲁棒解决方案,我们认为它优于基于期望的方法,并通过广泛的模拟比较了两种方案。
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