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首页> 外文期刊>Wireless Communications, IEEE Transactions on >Optimal Power Allocation and User Scheduling in Multicell Networks: Base Station Cooperation Using a Game-Theoretic Approach
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Optimal Power Allocation and User Scheduling in Multicell Networks: Base Station Cooperation Using a Game-Theoretic Approach

机译:多小区网络中的最佳功率分配和用户调度:使用博弈论方法的基站协作

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摘要

This paper proposes a novel base station (BS) coordination approach for intercell interference mitigation in the orthogonal frequency-division multiple access based cellular networks. Specifically, we first propose a new performance metric for evaluating end user's quality of experience (QoE), which jointly considers spectrum efficiency, user fairness, and service satisfaction. Interference graph is applied here to capture and analyze the interactions between BSs. Then, a QoE-oriented resource allocation problem is formulated among BSs as a local cooperation game, where BSs are encouraged to cooperate with their peer nodes in the adjacent cells in user scheduling and power allocation. The existence of the joint-strategy Nash equilibrium (NE) has been proved, in which no BS player would unilaterally change its own strategy in user scheduling or power allocation. Furthermore, the NE in the formulated game is proved to lead to the global optimality of the network utility. Accordingly, we design an iterative searching algorithm to obtain the global optimum (i.e., the best NE) with an arbitrarily high probability in a decentralized manner, in which only local information exchange is needed. Theoretical analysis and simulation results both validate the convergence and optimality of the proposed algorithm with fairness improvement.
机译:本文提出了一种新的基站(BS)协调方法,用于在基于正交频分多址蜂窝网络中缓解小区间干扰。具体来说,我们首先提出了一种新的性能指标,用于评估最终用户的体验质量(QoE),该指标共同考虑了频谱效率,用户公平性和服务满意度。干扰图在这里用于捕获和分析基站之间的交互。然后,在基站之间提出了一种面向QoE的资源分配问题,作为一种本地合作博弈,其中鼓励基站与相邻小区中的对等节点协作进行用户调度和功率分配。联合策略纳什均衡(NE)的存在已得到证明,在这种策略中,没有BS参与者会单方面更改其在用户调度或功率分配中的策略。此外,事实证明,制定的博弈中的NE导致网络实用程序的全局最优性。因此,我们设计了一种迭代搜索算法,以分散的方式以任意高的概率获得全局最优(即,最佳NE),其中仅需要本地信息交换。理论分析和仿真结果均验证了所提算法的收敛性和最优性,同时提高了公平性。

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