Enhanced distributed cooperative spectrum sensing for cognitive radio networks

Cognitive radio will gain acceptance only when the primary detection model is accurate to insure no interference to primary system. Cooperative sensing for primary detection is degraded by the reliability of local node sensing in high fading environments. Further, managing the control channel and fusion node is problematic aspect. For instance, to ensure the local sensing is reported correctly to fusion centre requires very low bit error rate (BER) channel. Another issue, that reporting channel needs large bandwidth to carry the reporting traffics. In order to improve the sensing performance and reduce the reporting error, a distributed architecture for processing and fusion of sensing information is considered. This thesis proposes an adaptive and distributed detection threshold based on maintained probability of false alarm to increase reliability of sensing under Rayleigh fading channel. The link quality status of the sensing channel of the candidate nodes is used to determine the detection threshold dynamically and the reporting link status is used for dynamic selection of fusion node for the distributed cooperative sensing. Furthermore a dynamic TDMA MAC is proposed for media access and information exchange where the noise estimation is also used for the nodes reporting scheduling; this method increases the sensing time for the later scheduled cognitive radios. The proposed distributed scheme shows a significant improvement in the overall detection readability. The probability of detection, and bit error rate (BER) were used as performance metrics in the analytical and simulation results to validate the proposed method over the direct cooperation and non-cooperative sensing. Also analytical formulation with possible candidate selection criteria is used to investigate and optimize the distributed cooperation gain. The results show that by employing such distribution and selection technique, the reporting error due to the fading channel is reduced up to 42% based on number of candidate nodes. Results also shown that the method significantly improved the sensing performance by increase the probability of detection up to 0.9 at <0.1 probability of false alarm. Sensitivity requirement is reduced dramatically by more than 95% with varying number of nodes and probability of detection. Receiver operation characteristic (ROC) curve with the parameters and performance achieved verified that the probability of detection Pd can be improved significantly while maintaining probability of false alarm <0.1.

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