Abstract

In order to save the channel resource and transmitting power, the original signal can be compressed by compressed sensing theory and then transmitted in the channel when it is wideband and compressive. However, in cognitive radio network, the secondary users may still not have a strong sampling ability and on the other hand the data quantity is still too large. To solve this problem, this paper proposes a spectrum sensing algorithm for compressed sampling transmitting signal based on matched filter detection and compressed sensing theory. By adopting the compressed sensing technology, the data quantity in the receiving terminal is reduced greatly and on the other hand, the execution speed is enhanced. Furthermore, the simulation results show that the detection performance of proposed algorithm is better than conventional energy detection algorithm. The parameters which effect to the detection performance are theoretically analyzed in this paper and then demonstrated in the simulation.

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