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Decentralized Cross-Layer Optimization for Energy-Efficient Resource Allocation in HetNets

机译:分散跨层优化,用于Hetnets中的节能资源分配

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In this paper, we develop a joint physical and medium access control (MAC) layer optimization (JPMO) scheme based on game theory for energy-efficient resource allocation and interference management in heterogeneous networks (HetNets). In HetNets, cross-tier interference and co-tier interference significantly limit the network performance. Moreover, when each user only has its own channel state information and chooses its transmission policy independently without any coordination mechanism, it will result in the network collapse or waste of channel resources. To maximize the network efficiency, we develop the JPMO scheme through pricing mechanism from the perspective of game theory. Then we transform this scheme into a two-stage Stackelberg game, in which macrocell determines the transmission policy in MAC layer first, and then SCs perform EE power allocation in physical layer. Simulation results validate the effectiveness of the proposed scheme.
机译:在本文中,我们开发了基于基于博弈论的联合物理和中型访问控制(MAC)层优化(JPMO)方案,用于异构网络中的节能资源分配和干扰管理(Hetnets)。在Hetnets中,交叉层干扰和共级干扰显着限制了网络性能。此外,当每个用户只有其自己的信道状态信息并且独立选择其传输策略而没有任何协调机制,它将导致网络折叠或浪费信道资源。为了最大限度地提高网络效率,我们通过博弈论的角度通过定价机制开发JPMO方案。然后,我们将此方案转换为两级Stackelberg游戏,其中Macrocell首先确定MAC层中的传输策略,然后SCS在物理层中执行EE功率分配。仿真结果验证了拟议方案的有效性。

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