  Energy harvesting (EH), which explores renewable energy as a supplementary
power source, is a promising 5G technology to support the huge energy demand of
heterogeneous cellular networks (HCN). However, the random arrival of renewable
energy brings great challenges to network management. By adjusting the
distribution of traffic load in spatial domain, traffic shaping helps to
balance the cell-level power demand and supply, and thus improves the
utilization of renewable energy. In this paper, we investigate the power saving
performance of traffic shaping in an analytical way, based on the statistic
information of energy arrival and traffic load. Specifically, an energy-optimal
traffic shaping scheme (EOTS) is devised for HCNs with EH, whereby the on-off
state of the off-grid small cell and the amount of offloading traffic are
adjusted dynamically with the energy variation, to minimize the on-grid power
consumption. Numerical results are given to demonstrate that for the daily
traffic and solar energy profiles, EOTS scheme can significantly reduce the
energy consumption, compared with the greedy method where users are always
offloaded to the off-grid small cell with priority.
