论文标题
多运营商认知通信系统的分布式资源分配算法
Distributed Resource Allocation Algorithms for Multi-Operator Cognitive Communication Systems
论文作者
论文摘要
我们在认知无线电(CR)通信系统中解决了与现有主要运营商共享频谱的资源分配(RA)问题。 RA问题的主要挑战是优化问题中出现的操作员协调,因此主要用户的汇总干扰(PUS)不超过目标阈值。虽然如果集中式单元可以访问所有二级操作员的信息,则很容易解决此问题,但在现实情况下,它变得具有挑战性。在本文中,考虑到卫星设置,我们通过提出两种方法来降低二级运营商之间的信息交换水平来减轻此问题。在第一种方法中,我们基于部分信息共享方法制定了RA方案,该方法可以在二级操作员之间进行分布式优化。在第二种方法中,运营商仅在二级运营商中本地执行了干扰级别和RA的贡献,而不是交换二级用户(SUS)信息。在这种情况下,这两种方法首次提供了绩效与操作员信息交换水平之间的权衡。通过数值模拟,我们解释了这种权衡,并说明了部分信息交换所带来的惩罚。
We address the problem of resource allocation (RA) in a cognitive radio (CR) communication system with multiple secondary operators sharing spectrum with an incumbent primary operator. The key challenge of the RA problem is the inter-operator coordination arising in the optimization problem so that the aggregated interference at the primary users (PUs) does not exceed the target threshold. While this problem is easily solvable if a centralized unit could access information of all secondary operators, it becomes challenging in a realistic scenario. In this paper, considering a satellite setting, we alleviate this problem by proposing two approaches to reduce the information exchange level among the secondary operators. In the first approach, we formulate an RA scheme based on a partial information sharing method which enables distributed optimization across secondary operators. In the second approach, instead of exchanging secondary users (SUs) information, the operators only exchange their contributions of the interference-level and RA is performed locally across secondary operators. These two approaches, for the first time in this context, provide a trade-off between performance and level of inter-operator information exchange. Through the numerical simulations, we explain this trade-off and illustrate the penalty resulting from partial information exchange.