An Improved Dual Threshold DMM Cooperative Spectrum Sensing Algorithm

For problems of eigenvalue-based dual thresholds spectrum sensing algorithms overlooking the reliability difference between second users (SU) and its high expense of decisions, a dual threshold DMM cooperative spectrum sensing algorithm (DT-CDMM) based on credibility was proposed to improve the sensing performance. Based on difference between maximum and minimum eigenvaluealgorithm (DMM), a dual thresholds DMM spectrum sensing algorithm based on limiting eigenvalue distribution was used as SU's local sensing, a triggered mechanism combined with soft and hard decisions was established to cut the system expenses, the final decision was obtained via the weighting of SU's sensing performance and local credibility, and an self-adaption compensation for hard decisions was applied to proposed algorithm. Theory analysis and simulations shown the DT-CDMM has performance improvement over classical dual thresholds algorithms with noise uncertainty.