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首页> 外文期刊>International journal of online engineering >A Robust Power Allocation Scheme in Ad-Hoc Cognitive Radio Networks
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A Robust Power Allocation Scheme in Ad-Hoc Cognitive Radio Networks

机译:Ad-Hoc认知无线电网络中的鲁棒功率分配方案

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摘要

We investigate the secondary users (SUs) power allocation in ad-hoc cognitive radio networks, considering an underlay paradigm where SUs can access the licensed spectrum owned by the primary users (PUs), if the total power to SUs and the interference power threshold from PUs and the signal-to-interference-noise-ratio (SINR) requirements of SUs are guaranteed. While prevalent works about distributed resources allocation algorithms are mainly focused on power allocation under the consideration of many practical limitations, which may not be the case in practice. We assume that SUs also are needed to satisfy heterogenous constraints with different positions by taking the fairness of SUs into account. Moreover, we develop a weighted robust distributed power allocation scheme to guarantees the fairness of SUs. Techniques from robust optimization theory are used to study an objective formulation with infinite numbers of constraints. The optimal solution is obtained by using Lagrange dual method, and the Lagrange multiplier is solved by the sub-gradient update algorithm. The feasibility and availability of our proposed power allocation scheme is confirmed by numerical results.
机译:我们研究了临时认知无线电网络中的次用户(SU)功率分配,考虑了一个底层范式,如果SU的总功率和来自该用户的干扰功率阈值,则SU可以访问主要用户(PU)拥有的许可频谱。保证了PU和SU的信号干扰噪声比(SINR)要求。尽管有关分布式资源分配算法的流行工作主要集中在考虑许多实际限制的功率分配上,但实际情况可能并非如此。我们假设通过考虑SU的公平性,还需要SU来满足不同位置的异构约束。此外,我们开发了加权鲁棒的分布式功率分配方案,以确保SU的公平性。鲁棒优化理论的技术用于研究具有无限数量约束的目标公式。通过使用拉格朗日对偶法获得最优解,并通过子梯度更新算法求解拉格朗日乘数。数值结果证实了我们提出的功率分配方案的可行性和可用性。

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