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On Throughput Region for Primary and Secondary Networks With Node-Level Cooperation

机译:节点级协作的主备网络吞吐量区域

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Cooperation has become an essential element in spectrum sharing between the primary and secondary networks. A new trend in cooperation is to allow the primary and secondary networks to cooperate on the node level for data forwarding. This new paradigm allows to pool network resources from both the primary and secondary networks and allows users in each network to access a much richer network infrastructure in a combined network. This paper offers an in-depth study of such node-level cooperation by explaining its optimal throughput curve—the maximum achievable throughput for both the primary and secondary users. We formulate the problem as a multicriteria optimization problem with the goal of maximizing the throughput of both the primary and secondary users. Through a novel approach based on weighted Chebyshev norm, we transform the multicriteria optimization problem into a single criteria optimization problem and find a sequence of Pareto-optimal points iteratively. Based on the Pareto-optimal points, we construct the throughput curve and show that it provides an ε -approximation to the optimal curve. We prove some important properties of the optimal throughput curve. Through a case study, we show that the throughput region (the area under the throughput curve) under node-level cooperation is substantially larger than that when there is no node-level cooperation.
机译:合作已成为主要网络和次要网络之间频谱共享的基本要素。协作的新趋势是允许主网络和辅助网络在节点级别进行协作以进行数据转发。这种新的范例允许从主网络和辅助网络中合并网络资源,并允许每个网络中的用户访问组合网络中更丰富的网络基础结构。本文通过解释其最佳吞吐量曲线(主要和次要用户均可实现的最大吞吐量),对此类节点级合作进行了深入研究。我们将该问题表述为多准则优化问题,目的是最大程度地提高主要和次要用户的吞吐量。通过基于加权Chebyshev范数的新颖方法,我们将多准则优化问题转换为单准则优化问题,并迭代找到一系列Pareto最优点。基于帕累托最优点,我们构建了吞吐量曲线,并表明它为最优曲线提供了ε-逼近。我们证明了最佳吞吐量曲线的一些重要特性。通过案例研究,我们发现节点级合作下的吞吐量区域(吞吐量曲线下的面积)比没有节点级合作时的吞吐量区域大得多。

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