Interference efficiency: A new concept to analyze the performance of cognitive radio networks
Interference efficiency: A new concept to analyze the performance of cognitive radio networks
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DOI：
10.1109/iccw.2017.7962806
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发表时间：
2017-05
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通讯作者：
Mohammad Robat Mili;Leila Musavian
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文献类型：
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作者：
Mohammad Robat Mili;Leila Musavian
在本文中，我们开发并分析了一种新的性能指标，称为干扰效率（IE），它显示了底层认知无线电网络（CRN）中施加在主用户（pu）上的每单位干扰能量的传输位数。具体而言，我们开发了一个框架，以最大化具有多个辅助用户（su）的CRN的IE，同时满足PU接收器的平均干扰功率，su的总发射功率和su的最小遍历率的目标约束。为此，我们制定了一个多目标优化问题（MOP），其目的是实现多个单元的最大遍历和速率和最小的平均干扰功率对主接收机。我们展示了如何从所提出的MOP的Pareto最优区域中提取ie最大化问题的最优点。首先用加权和法将MOP转化为单目标问题（SOP）来求解。该公式的SOP是一个非凸优化问题，我们使用增广拉格朗日方法求解它。增广拉格朗日由一类惩罚二次项组成，使问题局部凸化，消除了对偶间隙。数值结果证实了我们的理论分析。
In this paper, we develop and analyze a novel performance metric, called interference efficiency (IE), that shows the number of transmitted bits per unit of interference energy imposed on the primary users (PUs) in an underlay cognitive radio network (CRN). Specifically, we develop a framework to maximize the IE of a CRN with multiple secondary users (SUs) while satisfying target constraints on the average interference power on PU receiver, total SUs transmit power and minimum ergodic rate for the SUs. In doing so, we formulate a multiobjective optimization problem (MOP), that aims to achieve the maximum ergodic sum rate of multiple SUs and the minimum average interference power on the primary receiver. We show how the optimal point for the IE-maximization problem can be extracted from the Pareto optimal region of the proposed MOP. The MOP is solved by first transferrin g it into a single objective problem (SOP) using a weighted sum method. The formulated SOP is a nonconvex optimization problem and we solve it using an augmented Lagrange approach. The augmented Lagrangian which consists of a penalty-like quadratic terms changes the problem to become locally convex and eliminates the duality gap. Numerical results are conducted to corroborate our theoretical analysis.