As the number of primary users are increased in huge number detecting the presence of more than one primary user in the cognitive area network will increase the quality of the spectrum usage for continuous usage. In Dynamic spectrum sharing the cognitive user often undergo the process of leaving the primary user spectrum as soon as the primary user occupies the spectrum. This immediate leaving from the primary user spectrum will affect the ongoing communication of the cognitive user. So cognitive users need to monitor the neighboring multiple primary user spectrum to manage the discontinuity in the communication. In this paper we have implemented the multi band spectrum sensing of the primary user using Two National Instruments USRP 2943R Transceivers (1.1GHz-6Ghz) to sense the spectrum using energy-based spectrum sensing technique in LabVIEW Platform. The primary user spectrum sensing is done based on the threshold value updated manually and adaptive method. The results are very promising for high threshold values compare to low threshold values.

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Sensing time plays an important role in Cognitive radio functionalities. The main approach of this paper is to predict the pattern of the primary user spectrum in order to reduce the battery power of the cognitive user in sensing the primary user spectrum continuously. We have developed a CNN-LSTN based model for predicting a traffic method with more accuracy. This method is relatively tested for different frequency bands of existing mobile operators using the deep radio.