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Centralized and Game Theoretical Solutions of Joint Source and Relay Power Allocation for AF Relay Based Network

机译:基于AF中继的网络源与中继功率联合分配的集中和博弈论解决方案

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Relaying is an emerging technique for 3G/4G high bandwidth networks in order to improve the capacity of edge nodes. As the deployment cost is high, there might be a few number of relay nodes in the cell which can help the edge nodes to transmit their data. From this perspective, one of the key problems in a relay equipped node is to make decision which edge nodes to be helped and how much power need to be disseminated among them in order to maximize the system capacity. This problem is formulated as an optimization problem given individual node and total available power constraints. The objective function of the formulated problem is non-convex, and we solve this using geometric programming (GP)-based method. Since the solution of this problem is computationally expensive, we propose a low complexity suboptimal solution. Having noticed the selfless nature of the sources in the centralized solution, we also provide a game theoretical solution. Two separate Stackelberg games are required to solve this power allocation problem. Moreover, given the total power constraint, a centralized entity is necessary to connect these two games. For assigning power among the sources, the centralized entity plays the buyer level game, whereas the sources act as power sellers. On the other hand, to disseminate relay power among the sources, roles of the players are just interchanged. Besides, before staring the game, the centralized entity determines, of total power, how much is for the transmit operation of the sources and how much is for their relay operation. We show that there is a unique Stackelberg Equilibrium (SE) for both games under certain convergence condition. Finally, the proposed game theoretical solution can achieve comparable performance in terms of resource allocation with the centralized optimal one.
机译:中继是3G / 4G高带宽网络的新兴技术,目的是提高边缘节点的容量。由于部署成本很高,因此小区中可能有几个中继节点,可以帮助边缘节点传输其数据。从这个角度来看,配备中继的节点中的关键问题之一是确定要帮助的边缘节点以及需要在它们之间分配多少功率以最大化系统容量。给定单个节点和总可用功率约束,此问题被公式化为优化问题。公式化问题的目标函数是非凸函数,我们使用基于几何规划(GP)的方法来解决该问题。由于此问题的解决方案计算量很大,因此我们提出了一种低复杂度次优解决方案。在集中式解决方案中注意到了源代码的无私性之后,我们还提供了一种博弈论解决方案。需要两个单独的Stackelberg游戏来解决此功率分配问题。而且,给定总功率约束,必须有一个集中的实体来连接这两个游戏。为了在资源之间分配权力,集中式实体会进行买方级别的游戏,而资源则充当卖方。另一方面,为了在信号源之间分配中继功率,只需互换播放器的角色。此外,在注视游戏之前,集中式实体确定总功率中,源的发送操作需要多少,中继操作需要多少。我们证明在一定收敛条件下,两种游戏都有一个独特的Stackelberg平衡(SE)。最后,所提出的博弈论解决方案在资源分配方面可以达到与集中式最优解决方案相当的性能。

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