Optimization of sensing and detection in cognitive radio using energy based algorithm and quantized data fusion

With the evolution of cognitive radio, there are continuously an ongoing development to make it more efficient. More stress is given on the Sensing and Management of cognitive radio as these plays an important role for the allocation and managing of secondary users in different channels. For Cognitive Radio, the main issue is to sense and then identify all spectrum holes present in the environment. In this paper, we have studied the behavior of primary signals and its corresponding detection in secondary nodes and improving the error rate performance with varying threshold. In the proposed method, the false alarm probability is compared and made it improved by using energy based algorithm which were used in radar detection techniques.