Optimal power allocation in dispersed cognitive radio systems with carrier aggregation

F. Foukalas, T. Khattab
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引用次数: 1

Abstract

In this paper, we investigate the optimal power allocation problem in dispersed cognitive radios with carrier aggregation. To this end, we model the carrier aggregation using an i - th frequency diversity policy, wherein each component carrier is provided with a maximal ratio combining. An ascending order is employed for the aggregation using maximal ratio combining receiver. Additionally, due to the dispersed nature of the channels, we assume an independent but non-identically distributed (i.n.i.d.) η - μ distribution for each channel branch. Having defined this model, we formulate the maximization problem over the transmit power of each CC with frequency diversity provision over the heterogeneous fading channels. The problem is solved using alternating direction method of multipliers (ADMM) as a dual decomposition application providing robustness. Distributed (without consensus) and centralized (with consensus) ADMM algorithms are devised and the corresponding simulation results are discussed. Simulation results corroborates the performance gain of the proposed ADMM solution both in terms of iterations and rate gain per CC.
基于载波聚合的分散认知无线电系统的最优功率分配
研究了具有载波聚合的分散认知无线电的最优功率分配问题。为此,我们使用频率分集策略对载波聚合进行建模,其中每个分量载波具有最大比例组合。采用最大比值结合接收端,按升序进行聚合。此外,由于通道的分散性,我们假设每个通道分支具有独立但非同分布(i.n.i.d) η - μ分布。定义了该模型后,我们提出了在异构衰落信道上提供频率分集的每个CC的发射功率最大化问题。采用交替方向乘法器(ADMM)作为一种具有鲁棒性的对偶分解方法来解决该问题。设计了分布式(无共识)和集中式(有共识)ADMM算法,并讨论了相应的仿真结果。仿真结果证实了所提出的ADMM解决方案在迭代和每CC速率增益方面的性能增益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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