The invention relates to the field of
cognitive radio communication and provides a multi-layer distributed combined spectrum sensing
algorithm based on a
Dirichlet process so as to realize dynamic spectrum sensing. The
sensing data acquired by secondary users in a plurality of hierarchical centers is fused to search the optimized sensing information. The automatic data packet is realized by employing the
Dirichlet process, a shared hyper-parameter and a corresponding divergent probability in each packet are estimated by a bayesian model, the hyper-parameter is acquired by employing a standard
Viterbi algorithm, and the hyper-parameter is compared with a
decision threshold value to acquire a final spectrum decision result so as to determine whether a channel is available. Due to the design, the space diversity information of the
compressed sensing data is fully considered, and the uncertainty of an individual secondary user on the
compressed sensing data is reduced, so that the normalized mean squared error performance is high, the
compressed sensing data information in each hierarchical center can be effectively obtained through the
algorithm, high accurate detection probability and low
false alarm probability are acquired, and the spectrum sensing performance is improved.