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Optimal power allocation for variable-hop cooperative relay in cognitive networks

机译:认知网络中可变跳跃协作继电器的最优功率分配

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In this work, we present an optimal power allocation scheme dedicated for variable-hop cooperative relays in cognitive networks, which consists of Secondary users (SUs) operating in Amplify-and-Forward (AF) mode, with a Primary user (PU) receiver nearby. In order to assure the quality of service (QoS) for PU, transmit power of cognitive radio (CR) nodes must be tightly controlled which leads to narrow communication range. The issue of minimal feasible hop count Nmin and energy-saving with relays which can only cause limited interference to PU are considered to enable the communication between remote nodes under the constraint of minimal signal to noise ratio (SNR) γth. Closed-form solution for the optimal power allocation scheme is obtained by Lagrangian algorithm along with an O(N) complexity dichotomy method to achieve Nmin. We prove that the energy consumption in the system is reduced with the growth of N by both theoretical derivation and extensive simulation, and the general relation between Nmin and γth.
机译:在这项工作中,我们提出了一种专用于认知网络中的可变跳跃协作继电器的最佳功率分配方案,其包括以放大和向前(AF)模式操作的二级用户(SUS),其中主要用户(PU)接收器附近。为了确保PU的服务质量(QoS),必须紧密地控制认知无线电(CR)节点的发射功率,这导致通信范围窄。最小可行跳数的问题和利用继电器的节能,其只能对PU引起有限的干扰,以便在最小信噪比(SNR)γth的限制下实现远程节点之间的通信。用于最佳功率分配方案的闭合方案是由拉格朗日算法获得的,以及o(n)复杂性二分法方法来实现nmin。我们证明系统中的能量消耗随着理论推导和广泛的模拟的增长,以及Nmin和γth之间的一般关系。

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