  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.
