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首页> 外文期刊>Quality Control, Transactions >Distributed ABS-Slot Access in Dense Heterogeneous Networks: A Potential Game Approach With Generalized Interference Model
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Distributed ABS-Slot Access in Dense Heterogeneous Networks: A Potential Game Approach With Generalized Interference Model

机译:密集异构网络中的分布式ABS时隙访问:具有广义干扰模型的潜在博弈方法

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摘要

This paper investigates the problem of almost blank subframe (ABS)-slot access in the heterogeneous networks to optimize network performance under the ABS scheme. Since maximizing network throughput requires global information and is not feasible in large scale or dense networks, the problem is solved from an interference minimization perspective after investigating the inherent relationship between local interference and achievable throughput. Since traditional binary interference model does not consider accumulated interference and thus results in inaccuracy, we take the accumulated interference into account and propose a generalized interference model, in which small cells are classified into different distant neighborhoods. An interference minimization game is formulated and is then proved to be an exact potential game, which has at least one pure Nash equilibrium (NE), and the best pure strategy NE point is a global optimum of minimizing aggregate interference. Combining the relationship between throughput and interference, the throughput maximization problem is proved to be an ordinal potential game, which possesses nice properties as well. A distributed algorithm is proposed to reach the NE, which minimizes the aggregate interference and maximizes the network throughput globally or locally. Furthermore, simulation results show that the proposed generalized interference model outperforms the traditional binary interference model.
机译:本文研究了异构网络中几乎空白的子帧(ABS)时隙访问问题,以优化ABS方案下的网络性能。由于最大化网络吞吐量需要全局信息,并且在大规模或密集网络中不可行,因此在研究本地干扰与可实现吞吐量之间的内在联系后,从干扰最小化的角度解决了该问题。由于传统的二进制干扰模型没有考虑累积干扰,因此会导致不准确,因此我们考虑了累积干扰,并提出了一种广义的干扰模型,其中将小小区划分为不同的远邻。制定了一个干扰最小化博弈,然后证明它是一个精确的潜在博弈,它具有至少一个纯纳什均衡(NE),而最佳的纯策略NE点是最小化总体干扰的全局最优解。结合吞吐量和干扰之间的关系,吞吐量最大化问题被证明是一个有序的潜在博弈,它也具有良好的性能。提出了一种分布式算法以达到NE,该算法可以最大程度地减少总干扰,并在全局或本地最大化网络吞吐量。仿真结果表明,提出的广义干扰模型优于传统的二进制干扰模型。

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