LAUSR

Small heterogeneous cells have been introduced to improve the system capacity and provide the ubiquitous service requirements. In order to make flexible deployment and management of massive small cells, the utilization of self-powered small cell base stations with energy harvesting (EH-SCBSs) is becoming a promising solution due to low-cost expenditure. However, the deployment of static EH-SCBSs entails several intractable challenges in terms of the randomness of renewable energy arrival and dynamics of traffic load with spatio-temporal fluctuation. To tackle these challenges, we develop a tractable framework of the location deployment and mobility management of EH-SCBSs with various traffic load distributions an environmental energy models. In this paper, the joint optimization problem for location deployment and mobile management is investigated for maximizing the total system utility of both users and network operators. Since the formulated problem is a NP-hard problem, we propose a low-complex algorithm that decouples the joint optimization into the location updating approach and the association matching approach. A suboptimal solution for the optimization problem can be guaranteed using the iteration of two stage approaches. Performance evaluation shows that the proposed schemes can efficiently solve the target problems while striking a better overall system utility, compared with other traditional deployment and management strategies.