Green small cell planning in smart cities under dynamic traffic demand

In smart cities, cellular network plays a crucial role to support connectivity anywhere and anytime. However, the communication demand brought by applications and services is hard to predict. Traffic in cellular networks might fluctuate heavily over time to time, which causes burden and waste under different traffic states. Recently, small cell was proposed to enhance spectrum efficiency and energy efficiency in cellular networks. However, how green the small cell network can be is still a question because of the accompanying interference. To meet this challenge, new green technologies should be developed. In this paper, we propose a green small cell planning scheme considering dynamic traffic states. First, we predefine a set of candidate locations for base stations (BSs) in a geographical area and generate a connection graph which contains all possible connections between BSs and user equipments (UEs). Then we adopt a heuristic to switch off small cell BSs (s-BSs) and update BS-UE connections iteratively. Finally we obtain a cell planning solution with energy efficiency without reducing spectrum efficiency and quality-ofservice (QoS) requirements. The simulation results show that our dynamic small cell planning scheme has low computational complexity and achieves a significant improvement in energy efficiency comparing with the static cell planning scheme.