GreenDelivery: Proactive Content Caching and Push with Energy-Harvesting-based Small Cells

The explosive growth of mobile multimedia traffic calls for scalable wireless access with high quality of service and low energy cost. Motivated by the emerging energy harvesting communications, and the trend of caching multimedia contents at the access edge and user terminals, we propose a paradigm-shift framework, namely GreenDelivery, enabling efficient content delivery with energy harvesting based small cells. To resolve the two-dimensional randomness of energy harvesting and content request arrivals, proactive caching and push are jointly optimized, with respect to the content popularity distribution and battery states. We thus develop a novel way of understanding the interplay between content and energy over time and space. Case studies are provided to show the substantial reduction of macro BS activities, and thus the related energy consumption from the power grid is reduced. Research issues of the proposed GreenDelivery framework are also discussed.Comment: 15 pages, 5 figures, accepted by IEEE Communications Magazin

Joint Deployment and Mobility Management of Energy Harvesting Small Cells in Heterogeneous Networks

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