Adaptive Double Threshold based Spectrum Sensing for Cognitive Radio Networks

Rapid growth of wireless communication and limited spectrum availability to support the applications and services, has led to the development of cognitive radio as promising solution to address the problem of spectrum scarcity. Spectrum sensing is one of the fundamental functions towards the implementation of the cognitive radio concept in wireless communication. In this paper, we present an adaptive double threshold based spectrum sensing utilizing fuzzy logic. It is shown that the proposed scheme achieves enhanced detection performance under noise uncertainty at a given Pf and also overcomes the problem of spectrum sensing failure. In this scheme, fuzzy logic is implemented at individual CR and the implementation of fusion center for decision making is done away with. Hence, overheads are reduced as compared to existing techniques. Probability of detection, probability of false alarm, and SNR are used as performance metrics. Simulation results shows that proposed scheme outperforms conventional and Cooperative sensing with single threshold, schemes by 33% and 16% at 5 dB SNR, respectively We have further implemented cooperative sensing along with the proposed scheme using fusion center and compared with recent techniques. It is further found that CSS with proposed scheme provides 8% , 33.3% and 16% improvement in detection as compared to that for cooperative CED with MRC and OR scheme and Hierarchical scheme at −8dB SNR, respectively. Since, in proposed scheme, only one bit decision is sent by each CR to fusion centre, hence communications overheads are also reduced as compared to MRC and Hierarchical scheme.