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Cognitive Networks Achieve Throughput Scaling of a Homogeneous Network

机译:认知网络实现同类网络的吞吐量扩展

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Two distinct, but overlapping, networks that operate at the same time, space, and frequency is considered. The first network consists of $n$ randomly distributed primary users, which form an ad hoc network. The second network again consists of $m$ randomly distributed ad hoc secondary users or cognitive users. The primary users have priority access to the spectrum and do not need to change their communication protocol in the presence of the secondary users. The secondary users, however, need to adjust their protocol based on knowledge about the locations of the primary users to bring little loss to the primary network's throughput. By introducing preservation regions around primary receivers, a modified multihop routing protocol is proposed for the cognitive users. Assuming $m=n^{beta}$ with $beta>1$, it is shown that the secondary network achieves almost the same throughput scaling law as a stand-alone network while the primary network throughput is subject to only a vanishingly small fractional loss. Specifically, the primary network achieves the sum throughput of order $n^{1/2}$ and, for any $delta>0$, the secondary network achieves the sum throughput of order $m^{1/2-delta}$ with an arbitrarily small fraction of outage. Thus, almost all secondary source-destination pairs can communicate at a rate of order $m^{-1/2-delta}$.
机译:考虑了两个不同但重叠的网络,它们在同一时间,空间和频率下运行。第一个网络由随机分布的$ n $个主要用户组成,形成一个自组织网络。第二个网络再次由随机分布的临时二级用户或认知用户组成。主要用户对频谱具有优先访问权,并且在次要用户在场时无需更改其通信协议。但是,次要用户需要基于有关主要用户位置的知识来调整其协议,以使主要网络的吞吐量几乎没有损失。通过引入主要接收者周围的保留区域,为认知用户提出了一种改进的多跳路由协议。假设$ m = n ^ {beta} $且$ beta> 1 $,则表明辅助网络实现了与独立网络几乎相同的吞吐量缩放定律,而主网络吞吐量仅受到很小一部分的影响失利。具体来说,主网络达到订单量$ n ^ {1/2} $的总吞吐量,并且对于任何$ delta> 0 $,辅助网络达到订单量$ m ^ {1 / 2-delta} $的总吞吐量中断的比例很小。因此,几乎所有第二源-目的地对都可以以$ m ^ {-1 / 2-delta} $的速率进行通信。

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