I. Introduction
Congestion in spectra of wireless networks is increasing with number of users. However, at times parts of the spectrum remain underutilized [2]. This gives rise to the need for algorithms that can dynamically share the available spectrum. In the scenario of cognitive radio, spectrum sharing allows cognitive radio users (secondary) to share the spectrum bands of the licensed users (primary). A key aspect of spectrum sharing is spectrum sensing [3]. Spectrum sharing involves white space detection based on which the secondary users (SUs) communicate. Since the primary users (PUs) opportunistically allow the secondary users to operate in an inactive frequency band originally allocated to the PUs, minimum time delay in spectrum sensing is desired [4]. Recent research efforts have been made towards designing high-quality spectrum-sensing devices and algorithms to characterize the radio frequency (RF) environment, particularly to recognize the modulation scheme. Distortion of the received signal due to channel fading effects makes modulation recognition a challenging task. Hence, an algorithm that models and corrects the distortion caused by the channel should improve modulation recognition.