Cognitive radio (CR) is a wireless technology developed to improve the usage in the spectrum frequency. Energy consumption is considered as a big problem in this technology, especially during a spectrum sensing. In this paper, we propose an algorithm to improve the energy consumption during the spectrum sensing. The theoretical analysis to calculate the amount of energy consumption, using the proposed method during sensing stage as well as the transmission stage during transmitting a local decision to the fusion center FC, are derived. The proposed algorithm is using energy detection technique to detect the presence or absence of the primary user (PU). The proposed algorithm consists of two stages: the coarse sensing stage and fine sensing stage. In the coarse sensing stage, all the channels in the band are sensed shortly and the channel that have maximum (or minimum) energy is identified to make a dense fine sensing for confirming the presence of the PU signal (or hole). The performance of the proposed algorithm is evaluated in two scenarios: non-cooperative, and cooperative in both the AWGN and Rayleigh fading channels. The simulation results show that the proposed method improves the energy consumption by about 40% at a low SNR values, when compared with the traditional methods based on a single sensing stage and more advanced method based on censoring and sequential censoring algorithms.
Adaptive Spectrum Sensing for Throughput Maximization of Cognitive Radio Networks in Fading Channels
