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A Hop-by-Hop Relay Selection Strategy in Multi-Hop Cognitive Relay Networks

机译:多跳认知继电器网络中的逐跳中继选择策略

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摘要

In this paper, a hop-by-hop relay selection strategy for multi-hop underlay cognitive relay networks (CRNs) is proposed. In each stage, relays that successfully decode the message from previous hop form a decoding set. Taking both maximum transmit power and maximum interference constraints into consideration, the relay in the decoding set which has the largest number of channels with an acceptable signal-to-noise ratio (SNR) level to the relays in the next stage is selected for retransmission. Therefore, relay selection in each stage only relies on channel state information (CSI) of the channels in that stage and does not require the CSI of any other stage. We analyze the performance of the proposed strategy in terms of end-to-end outage probability and throughput, and show that the results match those obtained from simulation closely. Moreover, we derive the asymptotic end-to-end outage probability of the proposed strategy when there is no upper bound on transmitters & x2019; power. We compare this strategy to other hop-by-hop strategies that have appeared recently in the literature and show that this strategy has the best performance in terms of outage probability and throughput. Finally it is shown that the outage probability and throughput of the proposed strategy are very close to that of exhaustive strategy which provides a lower bound for outage probability and an upper bound for throughput of all path selection strategies.
机译:在本文中,提出了用于多跳界面认知中继网络(CRNS)的逐跳中继选择策略。在每个阶段,成功解码来自先前跳的消息的继电器形成解码集。考虑最大发射功率和最大干扰约束,选择具有在下一阶段中的具有可接受的信噪比(SNR)电平的最大数量的通道的解码集中的继电器被选择用于重传。因此,每个阶段中的继电器选择仅依赖于该阶段中信道的信道状态信息(CSI),并且不需要任何其他级的CSI。我们在端到端中断概率和吞吐量方面分析了拟议的策略的表现,并表明结果与仿真收获的结果密切相关。此外,我们推导出<斜视>渐近的在发射机上没有上限时所提出的策略的最终进入概率;力量。我们将此策略与最近在文献中出现的其他跳跃策略进行比较,并表明该策略在中断概率和吞吐量方面具有最佳性能。最后,表明所提出的策略的停电概率和吞吐量非常接近完整策略,这为所有路径选择策略的吞吐量的中限提供了下限。

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