Entropy based spectrum sensing in cognitive radio

Cognitive radio (CR) is defined as an intelligent wireless communication, which has the capability of sensing and utilizing the underutilized spectrum resources. One of the key problems is how to efficiently and successfully detect the spectrum hole. In this paper, an entropy based technique for detection of primary users in cognitive radio networks with unknown noise and interference levels will be discussed. The likelihood ratio test will be used to examine the presence or absence of the primary user by comparing the empirical entropy of the received signal to a suitable threshold. In this paper, we will assume the primary user's signaling waveform is known by the cognitive radios and the matched-filter based detection will be specifically considered.