In spectrum sharing networks, a base station (BS)
needs to mitigate the interference to users associated with other
coexisting network in the same band. The BS can achieve this by
transmitting its downlink signal in the null space of channels
to such users. However, under a wideband scenario, the BS
needs to estimate null space matrices using the received signal
from such non-cooperative users in each frequency bin where
the users are active. To reduce the computational complexity
of this operation, we propose a frequency clustering algorithm
that exploits the channel correlations among adjacent frequency
bins. The proposed algorithm forms clusters of frequency bins
with correlated channel vectors without prior knowledge of
the channels and obtains a single null space matrix for each
cluster. We show that the number of matrices and the number
of eigenvalue decompositions required to obtain the null space
significantly reduce using the proposed clustering algorithm.