4.7 Article

Online Resource Management of Heterogeneous Cellular Networks Powered by Grid-Connected Smart Micro Grids

期刊

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS
卷 21, 期 10, 页码 8416-8430

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TWC.2022.3165975

关键词

Renewable energy sources; Costs; Resource management; Wireless communication; Optimization; Cellular networks; Smart grids; Heterogeneous cellular networks; grid-connected smart micro grids; online resource management; admission control; power allocation; energy sharing

资金

  1. National Natural Science Foundation of China [62001238]
  2. Open Research Fund of National Mobile Communications Research Laboratory, Southeast University [2022D11]
  3. Chengdu Chongqing Economic Circle Science Technology Innovation Project (CYSTIP) [KJCXZD2020026]

向作者/读者索取更多资源

This paper investigates the long-term average total energy cost minimization problem in Heterogeneous Cellular Networks powered by Grid-connected Smart Micro Grids. The proposed CAORM algorithm outperforms benchmarks in reducing total energy cost and making appropriate decisions according to different unit costs of renewable energy.
This paper investigates a long-term average total energy cost minimization problem via resource management, including admission control, power allocation, and Energy Sharing (ES) of renewable energy in Heterogeneous Cellular Networks powered by Grid-connected Smart Micro Grids (GSMG-HCNs). In GSMG-HCNs, both renewable and grid energy power the base stations. Unlike existing works, we consider the cost of both renewable and grid energy and formulate the power line loss process caused by ES into our model. To solve the proposed problem, we transform it into a real-time issue by the Lyapunov technique. The proposed Cost-Aware Online Resource Management (CAORM) algorithm decouples the real-time issue into two sub-problems, one of which is linear and the other is addressed based on the successive convex approximation approach. We theoretically prove the asymptotic optimality of the CAORM algorithm and a tradeoff between the average total energy cost and the average queue length. Simulation results reveal that the CAORM algorithm outperforms benchmarks in reducing total energy cost and can make appropriate decisions according to different unit costs of renewable energy. Besides, the designed distance-related ES loss rate can help obtain better solutions with lower ES losses.

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