Analysis of Spectrum Occupancy using Naïve Bayesian Classifier
Aman Kumar Mishra1, P. Vijaykumar2

1Aman Kumar Mishra, Department of ECE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
2Dr. P. Vijaykumar, Associate Professor, Department of ECE, SRM Institute of Science and Technology, Chennai (Tamil Nadu), India.
Manuscript received on 13 December 2018 | Revised Manuscript received on 25 December 2018 | Manuscript Published on 24 January 2019 | PP: 115-117 | Volume-7 Issue-4S2 December 2018 | Retrieval Number: Es2048017519/19©BEIESP
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Abstract: This work evaluates spectrum occupancy in cognitive radio network (CRN) based on naïve Bayesian classifier (NBC). It considers OFDM based users as primary users(PU) and 64- QAM based user as secondary user(SU). The motivation for this work is the classification problem in spectrum sensing, wherein it becomes important for secondary users (SUs) to sense free channel and use it for its own transmission/reception purpose given PU or SU are not present for effective utilization of spectrum that eventually leads to increased network throughput. Data were collected as constellation points of OFDM and 64- QAM at transmission power of -10dBm (0.1mw). Our proposed evaluation can be applied to D2D communication in next-generation heterogeneous network, where devices are considered as SUs and cellular based users are considered as PU. The complete architecture can be considered as decentralized network, where devices (SU) can use channel upon confirming the channel not being occupied by any other PU or SUs, this is believed to increase throughput of SUs. NBC is considered because it considers all features independents and gives good model for classification in future.
Keywords: Analysis Occupancy Classifier Communication Transmission.
Scope of the Article: Predictive Analysis