As small base stations (SBSs) are densely deployed to meet the explosive communication demands, the increases in energy consumption and carbon emissions call for the green and sustainable design of next-generation cellular networks. In this letter, we jointly optimize user association and resource allocation for a wireless network powered by a combined smart grid (SG) and renewable energy. We reduce the system transaction cost under constrained carbon emission while ensuring users’ quality-of-service (QoS). Generalizing the stochastic dual-subgradient method, an online resource allocation (ORA) approach is proposed to decide on beamforming and energy trading of SBSs online. A Multi-Attribute Decision Making (MADM)-based user association scheme is developed by leveraging the historical transaction cost of the SBSs derived by the ORA, energy harvesting rates, and distances between the SBSs and users through user mobility prediction. The feasibility and asymptotic optimality of the ORA are analyzed. Simulations show our algorithm cuts down the average system cost by 62.3% compared to the benchmarks.

中文翻译：

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受限碳排放下智能电网供电无线网络的联合用户关联与资源分配


随着小型基站 （SBS） 的密集部署以满足爆炸性的通信需求，能源消耗和碳排放的增加要求下一代蜂窝网络的绿色和可持续设计。在这封信中，我们共同优化了由智能电网 （SG） 和可再生能源相结合的无线网络的用户关联和资源分配。我们在保证用户服务质量 （QoS） 的同时，在限制碳排放的情况下降低系统交易成本。推广随机双次梯度方法，提出了一种在线资源分配 （ORA） 方法来决定在线 SBS 的波束成形和能量交易。利用 ORA 得出的 SBS 历史交易成本、能量收集率以及 SBS 与用户之间的距离，通过用户移动预测，开发了一种基于多属性决策 （MADM） 的用户关联方案。分析了 ORA 的可行性和渐近最优性。模拟表明，与基准相比，我们的算法将平均系统成本降低了 62.3%。