Energy Sharing-Based Energy and User Joint Allocation Method in Heterogeneous Network
Energy Sharing-Based Energy and User Joint Allocation Method in Heterogeneous Network
复制标题
基于能源共享的异构网络能源与用户联合分配方法
DOI：
10.1109/access.2020.2975293
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发表时间：
2020-01-01
期刊：
影响因子：
3.9
通讯作者：
Chen, Zhixiong
中科院分区：
文献类型：
--
作者：
Han, Dongsheng;Li, Shijie;Chen, Zhixiong
异构网络作为第五代移动的通信系统的关键技术，可以有效解决通信系统中频谱资源紧张的问题。然而，随着基站（BS）的密集部署以及用户数量和通信数据规模的增长，BS的系统能耗给网络运营商带来了巨大的经济压力。因此，降低能耗和通信系统的成本成为迫切需要解决的问题。随着智能电网的发展，基站的可再生能源发电设备为解决这一问题提供了机会。然而，由于受天气因素的影响，可再生能源的生产率呈现出强烈的波动性。这种情况给通信系统的能量分配带来了新的挑战。因此，在异构无线网络中，基站之间建立能量共享链路，并以宏基站和微基站之间的距离为指标。提出了基于能耗的能量和用户联合分配方法和基于能量成本的能量和用户联合分配方法。将两个多目标优化问题转化为两个凸优化问题，利用凸优化工具箱求解最优分配策略。仿真结果表明，基于能耗的分配方法以能耗为优化目标，使共享链路的发送能量源尽可能少。这种方式减少了链路和系统的能量消耗。基于能量成本的分配方法从经济角度出发，考虑了能量价格的影响，利用共享链路，基于能量成本协调基站之间的能量分配，优化各时隙基站之间的能量分配。因此，该方法可以大幅度降低系统的能量成本。
Heterogeneous network, which is a key technology of fifth generation(5G) mobile communication system, can effectively solve the spectrum resource shortage in the communication system. However, with densified deployment of base stations (BSs) and growth of user quantity and communication data size, the system energy consumption of BSs has imposed enormous economic pressure on network operators. As a result, energy consumption decreases and cost of communication system becomes a problem that requires urgent solutions. Renewable energy power generation devices of BSs have provided an opportunity for solving this problem with the development of smart power grids. However, the production rate of renewable energy sources presents intense volatility because of the influence of weather factors. This condition brings new challenges to the energy allocation of communication system. Therefore, an energy sharing link between BSs was established in a heterogeneous wireless network, and the distance between macro-BS and micro-BS was taken as an index. The energy consumption-based energy and user joint allocation method and energy cost-based energy and user joint allocation method were proposed. The two multi-objective optimization problems were converted into two convex optimization problems, and the optimal allocation strategies were solved using convex optimization toolbox. Simulation results indicate that the energy consumption-based allocation method takes energy consumption as the optimization objective and makes the shared link transmit energy sources as few as possible. This way reduces energy consumptions of the link and the system. Starting from the economic angle, the energy cost-based allocation method considers the influence of energy price, coordinates energy allocation between BSs based on energy cost using the shared link, and optimizes energy allocation among BSs at each time slot. Therefore, the method can reduce the energy cost of the system by a large margin.