  Due to the increasing demand of capacity in wireless cellular networks, the
small cells such as pico and femto cells are becoming more popular to enjoy a
spatial reuse gain, and thus cells with different sizes are expected to coexist
in a complex manner. In such a heterogeneous environment, the role of
interference management (IM) becomes of more importance, but technical
challenges also increase, since the number of cell-edge users, suffering from
severe interference from the neighboring cells, will naturally grow. In order
to overcome low performance and/or high complexity of existing static and other
dynamic IM algorithms, we propose a novel low-complex and fully distributed IM
scheme, called REFIM, in the downlink of heterogeneous multi-cell networks. We
first formulate a general optimization problem that turns out to require
intractable computation complexity for global optimality. To have a practical
solution with low computational and signaling overhead, which is crucial for
low-cost small-cell solutions, e.g., femto cells, in REFIM, we decompose it
into per-BS problems based on the notion of reference user and reduce feedback
overhead over backhauls both temporally and spatially. We evaluate REFIM
through extensive simulations under various configurations, including the
scenarios from a real deployment of BSs. We show that, compared to the schemes
without IM, REFIM can yield more than 40% throughput improvement of cell-edge
users while increasing the overall performance by 10~107%. This is equal to
about 95% performance of the existing centralized IM algorithm that is known to
be near-optimal but hard to implement in practice due to prohibitive
complexity. We also present that as long as interference is managed well, the
spectrum sharing policy can outperform the best spectrum splitting policy where
the number of subchannels is optimally divided between macro and femto cells.
