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Activity Scheduling for Energy Harvesting Small Cells in 5G Wireless Communication Networks

机译:5G无线通信网络中的能量收集小型电池的活动调度

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For the upcoming fifth generation of wireless mobile communication networks, heterogeneous cellular architectures with a dense deployment of low-power small cells have been proposed to satisfy increasing data demands. Energy harvesting small cells, which operate with renewable energy sources such as solar energy and the potential for power storage, can be utilized to decrease the power consumption of the network if their activities are carefully scheduled based on the forecasted demand. In this work, we propose a novel approach for small cell energy management and activity scheduling, where not only the small cell activity but also the duration of time-slots in which the schedule is applied, are optimized. Cell load balancing is performed by solving separate mixed integer optimization problems, one each for activity optimization and for timescale optimization. Simulation results show that the proposed scheme is successful in finding an optimized small cell activity schedule for given energy levels and demand forecasts, and that there is a significant benefit achievable through the proposed timescale optimization approach.
机译:对于即将到来的第五代无线移动通信网络,已经提出了具有密集的低功率小小区的异构蜂窝架构,以满足增加的数据需求。能量收集与可再生能源(如太阳能和蓄电电源)运行的小电池,以降低网络的功耗,如果基于预测需求仔细安排他们的活动。在这项工作中,我们提出了一种用于小细胞能量管理和活动调度的新方法,而不仅是小的细胞活动,而且还优化了所应用时间表的时隙的持续时间。通过求解单独的混合整数优化问题,每个用于活动优化和时间尺度优化来执行单元负载平衡。仿真结果表明,该方案成功地寻找优化的小细胞活动时间表,了解给定能级和需求预测,通过所提出的时间尺度优化方法可以实现显着的益处。

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