Joint optimization for cell configuration and offloading in heterogeneous networks

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.