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Random fibonacci sequences and capacity/power scaling in cooperative multihop networks

机译：协作多跳网络中的随机斐波那契序列和容量/功率缩放

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In this paper, we analyze capacity and power scaling in multihop cooperative AF relay networks. An analytical framework for this task is developed by drawing a correspondence between random Fibonacci sequences and the end-to-end multihop system model. It turns out, the exponential growth rate of these interesting sequences can be employed to establish scaling laws, from which we conclude that it is possible to construct multihop cooperative AF networks that simultaneously avoid 1) exponential capacity decay and 2) exponential transmit power growth across the network. This is done by ensuring the network's Lyapunov exponent (a key observable studied in random dynamical system theory) is zero, which can be achieved by appropriately selecting the amplification factors at each of the relay nodes. Our results apply to both fixed-gain and variable-gain relaying. To conclude our work, we demonstrate the presented theory through numerical simulations.
机译：在本文中，我们分析了多跳协作AF中继网络的容量和功率缩放。通过绘制随机斐波那契序列与端到端多跳系统模型之间的对应关系，可以开发出用于此任务的分析框架。事实证明，这些有趣序列的指数增长率可用于建立缩放定律，从中我们得出结论，可以构建多跳协作AF网络，该网络同时避免1）指数容量衰减和2）跨越整个区域的指数发射功率增长网络。这是通过确保网络的Lyapunov指数（一个键可观察到的在随机动态系统理论研究）来完成是零，这可以通过在每个中继节点的适当选择放大系数来实现。我们的结果适用于固定增益和可变增益中继。总结我们的工作，我们通过数值模拟证明了提出的理论。

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