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Generalized Buffer-State-Based Relay Selection in Cooperative Cognitive Radio Networks

机译:合作认知无线电网络中的广义缓冲区中继选择

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摘要

In this paper, we propose a novel buffer-state-based relaying selection scheme in the context of cooperative cognitive radio networks (CRNs), supporting the primary and secondary networks. In the proposed scheme, both the effects of inter-network interference and fading are successfully suppressed by introducing a flexible link selection algorithm in the secondary network. More specifically, by relying on the broadcast nature of wireless communication channels between a source node and relay nodes in the secondary network, the associated source packet is shared among multiple relay nodes. This allows us to benefit from the additional degree of freedom. Furthermore, we consider the priority for link selection based on the buffer state of each relay node in the secondary network. This contributes to the avoidance of detrimental empty and full buffer states. Moreover, analytical bounds of the outage probability and the average packet delay are derived for the proposed scheme based on the Markov chain model, in order to verify the numerical results. The overhead required for a central coordinator of the secondary network to monitor channel state information and buffer states are also investigated. Our numerical results demonstrate that the proposed scheme achieves better outage and packet-delay performance than the conventional max-ratio-based scheme in the buffer-aided CRN.
机译:在本文中,我们提出了一种新的基于缓冲状态的中继选择方案,在协同认知无线电网络(CRNS)的上下文中,支持主和次要网络。在所提出的方案中,通过在二级网络中引入灵活的链路选择算法来成功地抑制网络间干扰和衰落的影响。更具体地,通过依赖于辅助网络中的源节点和中继节点之间的无线通信信道的广播性质,在多个中继节点之间共享相关联的源分组。这使我们可以从额外的自由度中受益。此外,我们考虑基于辅助网络中的每个中继节点的缓冲状态的链路选择的优先级。这有助于避免有害的空和全缓冲状态。此外,用于基于Markov链模型的所提出的方案导出停电概率和平均分组延迟的分析范围,以验证数值结果。还研究了用于监视信道状态信息和缓冲状态的二级网络的中央协调器所需的开销。我们的数值结果表明,所提出的方案比在缓冲辅助CRN中的传统最大比率的方案实现更好的中断和分组延迟性能。

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