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Joint optimization for cell configuration and offloading in heterogeneous networks

机译:联合优化异构网络中的小区配置和卸载

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To steadily gaining benefit from the exponential growth in mobile traffic, operators are eager to find solutions to maximize profits. Two very attractive strategies have been proposed to complement the existing macro cellular architecture: deploying low power bases stations and offloading data traffic to other networks. Each strategy has different costs and yields different benefits for operators. The offloading option could be cheaper in the short run; nevertheless, it might be more expensive in the long run than cell densification due to the varying cost. On the other hand, small cells, since having to be deployed in advance, may be underutilized or not fully meet future demands. In the latter case, offloading techniques can be used to increase capacity with additional costs. Further, uncertainty of future data demands and electricity prices also impact operators profitability, making the best network strategy difficult to achieve. To address such problem, an optimal cell configuration algorithm is proposed by formulating a stochastic programming model that considers both network design and data offloading. This algorithm can maximize the profit, under future demand and price uncertainty. Numerical studies are extensively performed in which the results show that operators' profits can be improved with our proposed algorithm.
机译:为了从移动通信量的指数增长中稳步获取收益,运营商渴望找到最大利润的解决方案。已经提出了两种非常有吸引力的策略来补充现有的宏蜂窝体系结构:部署低功率基站以及将数据业务卸载到其他网络。每种策略都有不同的成本,并为运营商带来不同的收益。在短期内,卸载选项可能会更便宜;但是,由于成本的变化,从长远来看,它可能比细胞致密化更昂贵。另一方面,小型蜂窝小区由于必须提前部署,因此可能未得到充分利用或无法完全满足未来的需求。在后一种情况下,可以使用卸载技术来增加容量,但要增加成本。此外,未来数据需求和电价的不确定性也影响运营商的盈利能力,使最佳网络策略难以实现。为了解决这个问题,通过制定考虑网络设计和数据卸载的随机规划模型,提出了一种最佳的小区配置算法。该算法可以在未来需求和价格不确定的情况下最大化利润。大量的数值研究表明,使用我们提出的算法可以提高运营商的利润。

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