Optimizing power limits for white space devices under a probability constraint on aggregated interference
Optimizing power limits for white space devices under a probability constraint on aggregated interference
复制标题
在聚合干扰概率约束下优化空白区设备的功率限制
DOI：
10.1109/dyspan.2012.6478131
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发表时间：
2012
期刊：
影响因子：
--
通讯作者：
Jonas Kronander
中科院分区：
文献类型：
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作者：
Y. Selén;Jonas Kronander
本文提出了一种解决共享一个频谱带的白色空间设备设置功率限制问题的方法。期望有效地利用可用的白色空间，同时还保护主系统免受有害干扰。通过最大化联合效用测量，例如，总容量。通过将有害聚合干扰的概率约束为低于定义的阈值来控制由白色空间设备对主系统造成的聚合干扰。首先，以最优化问题的形式给出了单个白色空间信道共享问题的数学公式。在对数正态衰落的常见假设下，聚合干扰的分布是未知的，优化问题变得不可行。计算上可行的近似的初始优化问题的制定，其中的分布的聚合干扰建模使用的Fenton-Wilkinson近似。我们得到的表达式，有效地解决简化的优化问题的数值求解器，包括梯度的约束和目标函数。我们通过模拟表明，简化的优化问题的解决方案通常满足原始的概率约束，具有良好的精度。此外，所得到的总容量值高于通常通过使用用于应对聚合干扰的固定裕度所能获得的值。我们还讨论了多信道扩展，它不仅能够处理相邻信道上工作的主系统的干扰，但也选择白色空间操作的信道，并决定相关的功率限制的联合问题。
This paper presents a solution to the problem of setting power limits for white space devices sharing a spectrum band. It is desired to utilize the available white space efficiently while also protecting the primary system from harmful interference. Power limits are set individually for each white space device by maximizing a joint utility measure, e.g., sum capacity. The aggregated interference caused by the white space devices to the primary system is controlled by constraining the probability of harmful aggregated interference to be below a defined threshold. First, the problem of single white space channel sharing is given a mathematical formulation in the form of an optimization problem. Under the common assumption of lognormal fading the distribution of the aggregate interference is unknown and the optimization problem becomes infeasible to solve. A computationally feasible approximation of the initial optimization problem is formulated in which the distribution of the aggregated interference is modeled using the Fenton-Wilkinson approximation. We derive the expressions needed for efficiently solving the simplified optimization problem with a numerical solver, including the gradients of the constraint and objective functions. We show by means of simulations that the solutions to the simplified optimization problem typically fulfill the original probability constraints with good precision. Further, the resulting sum-capacity values are higher than what can typically be obtained by using fixed margins for coping with the aggregate interference. We also discuss multi channel extensions which are able to handle not only interference to primary systems operating on adjacent channels, but also the joint problem of selecting the channels for white space operation and deciding the associated power limits.