  Managing radio spectrum resources is a crucial issue. The frequency
assignment problem (FAP) basically aims to allocate, in an efficient manner,
limited number of frequencies to communication links. Geographically close
links, however, cause interference, which complicates the assignment, imposing
frequency separation constraints. The FAP is closely related to the
graph-coloring problem and it is an NP-hard problem. In this paper, we propose
to incorporate the randomization into greedy and fast heuristics. As far as
being implemented, the proposed algorithms are very straight forward and are
without system parameters that need tuned. The proposed algorithms
significantly improve, quickly and effectively, the solutions obtained by
greedy algorithms in terms of the number of assigned frequencies and the range.
The enhanced versions of proposed algorithms perform close to the lower bounds
while running for a reasonable duration. Another novelty of our study is its
consideration of the net filter discrimination effects in the communication
model. Performance analysis is done by synthetic and measured data, where the
measurement data includes the effect of the real 3-dimensional (3D)
geographical features in the Daejeon region in Korea. In both cases, we observe
a significant improvement by employing randomized heuristics.
