Cognitive radio technology with reduced PAPR and complexity for IoT-based OFDM networks

Abstract

The principle target of an International Mobile Telecommunication (IMT) is to build a platform to advance the improvement of technology used in 5G and to inspire the support with the MNCs and organizations. The journey of 5th Generation initiated with 1G technology and has provided a massive improvement in today’s world. 5G technology on IMT provides the target to achieve ultra-high data rate, connectivity, reliability, lower latency, and lower data traffic. The usage of Orthogonal Frequency-Division Multiplexing (OFDM) system in 4G technology causes high Peak-to-Average Power Ratio (PAPR), complexity, and out-of-band radiation. To avoid these parameters, Filtered (F)-OFDM is exploited in 5G technology. The design becomes complex by the division of spectrum into non-contiguous spectrum fragments. So, resource block F-OFDM system using Internet of Things is proposed to convert non-contiguous spectrum into contiguous spectrum but the complexity remains the same. The proposed work of this paper is IoT-based RB-F-OFDM system along with inverse fast Walsh-Hadamard and Fourier transform to decrease the complexity and also, adaptive filter is exploited for retaining the actual (regular) grid to avoid signal information required for specifying a particular subband in the spectrum. Also, to enhance the quality of service, spectrum efficiency and cognitive radio system are used along with these techniques. Simulation result shows that proposed RB-Adaptive Filtered (AF)-OFDM provides low PAPR, high signal-to-interference ratio, and low bit error rate performance. The proposed RB-AF-OFDM system has the benefits of both RB-F-O FDM and adaptive F-OFDM so it further reduces the PAPR and complexity to the considerable value which is around 2.5.