Cooperative spectrum sensing in cognitive radio network consumes a large amount of energy during spectrum sensing and reporting. An energy-efficient reporting scheme called the reduced energy consumption scheme for reporting has been proposed to reduce energy consumption. In this scheme, all secondary users will sense the channel and make a local decision about the spectrum. All these local decisions are forwarded to a common node known as the fusion centre. This counts the presence or absence of the primary user based on the secondary user's local decisions. Whenever the counters count is greater than or equal to the threshold then the fusion centre sends a stop reporting feedback signal to the secondary users. In this way the energy consumption is reduced by diminishing the reporting secondary users and the energy efficiency is improved. The simulation and numerical results show a notable improvement in the energy efficiency of a reduced spectrum sensing scheme compared to the conventional spectrum sensing method.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Background: In cognitive radio networks, spectrum sensing plays an important role in identifying the underutilized spectrum bands. Conventional spectrum sensing using energy detection method uses single detection threshold, which degrades the detection performance. Method: Therefore double detection threshold has been proposed for spectrum sensing in the literature to improve the detection performance, but the performance depends on the region between two thresholds termed as confusion state. Hence to improve the overall detection performance new re-sensing scheme has been proposed in this paper by varying the difference between thresholds by an improvement factor K. Results: The proposed method improves the detection performance compared to the single threshold method and double threshold method. Conclusion: Simulation results show that the proposed method operates better than the single threshold energy detection method and improves the detection performance at low signal to noise ratios.