  Optimizing the cellular network's cell locations is one of the most
fundamental problems of network design. The general objective is to provide the
desired Quality-of-Service (QoS) with the minimum system cost. In order to meet
a growing appetite for mobile data services, heterogeneous networks have been
proposed as a cost- and energy-efficient method of improving local spectral
efficiency. Whilst unarticulated cell deployments can lead to localized
improvements, there is a significant risk posed to network-wide performance due
to the additional interference.
  The first part of the paper focuses on state-of-the-art modelling and
radio-planning methods based on stochastic geometry and Monte-Carlo
simulations, and the emerging automatic deployment prediction technique for
low-power nodes (LPNs) in heterogeneous networks. The technique advises a LPN
where it should be deployed, given certain knowledge of the network. The second
part of the paper focuses on algorithms that utilize interference and physical
environment knowledge to assist LPN deployment. The proposed techniques can not
only improve network performance, but also reduce radio-planning complexity,
capital expenditure, and energy consumption of the cellular network. The
theoretical work is supported by numerical results from system-level
simulations that employ real cellular network data and physical environments.
