PAPR and ISI reduction in cognitive radio network based 5G network using massive MIMO SC-FDMA ES

Abstract

Extended use of spectrum increased the number of users; this was the major cause to introduce Cognitive Radio Networks (CRN) which is designed to access the available spectrum effectively. Advanced telecommunication technology that is fifth-generation (5G) is inbuilt in CRNs. Fusion Center (FC) in CRN plays an important role in decision making for allocating available spectrum. A novel FC rotation (FCR) method is applied over FC to mitigate the occurrence of interference. Massive-Multiple Input Multiple Output (MaMi) system is used to enhance network performances to accommodate the huge participation of users by means of having a large number of antennas. Existing research works in CRN based 5G network fails to decrease intersymbol interference (ISI) and Peak-to-Average Power Ratio (PAPR). A novel Massive MIMO SC – FDMA ES is proposed in this paper to mitigate high PAPR values to enhance network performance. Our proposed work in CRN is experimentally designed using Network Simulator 3 from which the performances are evaluated. The extensive simulation result shows betterment in terms of channel capacity, reduction of PAPR, bit error rate and spectral efficiency.