Data for: Secondary Users Selection and Sparse Narrow-band Interference Mitigation in Cognitive Radio Networks

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and
services. To address this problem, different spectrum management techniques have been proposed
such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with
the licensed users. The main challenges in overlay CR networks are the identification and detection
of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore,
in this paper, we investigate the performance of an orthogonal frequency division multiplexing
(OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three
approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection
techniques are proposed in this paper to increase the expected signal to interference and noise ratio
based on full or partial knowledge of the channel state information (CSI). We also show that Distributed
selection techniques provide all the SUs equal chances to be selected without affecting the
selection diversity gain. General as well as simplified outage probability expressions are derived and
extensive simulations are conducted to evaluate the performance of the proposed techniques and
support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous
NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the
NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the
PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free
limit over practical ranges of NBI power levels.