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Joint cell selection and subchannel allocation for energy efficiency in small cell networks: A coalitional game

机译:联合小区选择和子信道分配以提高小型小区网络的能效:联合博弈

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摘要

Due to the dramatic growth of mobile data traffics, small cell network concept has been considered as a promising technique for mobile data offloading and enhancing spectrum utilization in the Long Term Evolution (LTE)-Advanced networks. Small cell networks allow the user equipment (UE) to transmit data through small cells instead of using only macro cells by reusing the same radio spectrum of the macro cells. A UE can select to transmit data through either a small cell or a macro cell. Moreover, the network needs to allocate the appropriate subchannel and the transmission power for each UE in the macro cells and small cells in order to avoid the harmful interference. In this paper, we focus on the problem of joint cell selection and resource allocation (i.e., subchannels and transmission power) for energy efficiency in small cell networks. A coalitional game is formulated to select cell and allocate resources where UEs in the same cell are considered to be in the same coalition. Small cell UEs (SUEs) are rational to maximize their individual utilities which equals to minimize the transmission power while transmission rate requirement is satisfied. To select subchannel, a greedy algorithm is used to assign a subchannel for an SUE to approximate an optimal assignment with low complexity. A distributed algorithm is also proposed to find stable coalitions. The simulation results show that the proposed scheme can achieve 31 percent in terms of power saving compared to the static random scheme.
机译:由于移动数据业务的急剧增长,小型蜂窝网络概念已被认为是一种有前途的技术,可用于移动数据卸载和增强高级长期演进(LTE)网络中的频谱利用率。小型小区网络允许用户设备(UE)通过小型小区传输数据,而不是通过重用宏小区的相同无线电频谱来仅使用宏小区。 UE可以选择通过小小区或宏小区来发送数据。此外,网络需要为宏小区和小型小区中的每个UE分配适当的子信道和传输功率,以便避免有害干扰。在本文中,我们专注于联合小区选择和资源分配(即子信道和传输功率)问题,以提高小型小区网络的能效。制定了联盟游戏来选择小区并分配资源,其中将同一小区中的UE视为处于同一联盟中。小小区UE(SUE)合理地最大化其各自的效用,这等于在满足传输速率要求的同时最小化传输功率。为了选择子信道,使用贪婪算法为SUE分配子信道以近似具有低复杂度的最优分配。还提出了一种分布式算法来找到稳定的联盟。仿真结果表明,与静态随机方案相比,该方案可以节省31%的功耗。

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