Analyses Hybrid Technique Detection Multiple Input Multiple Output 5G Waveforms

Abstract

The UFMC waveform is a type of physical layer, used by Cognitive Radio systems, to achieve reliable communication by using adaptive spectrum access. It is designed to provide interference-free communication without erasing the signals of the existing licensed users. The UFMC waveform is advantageous in Cognitive Radio networks because it can be very easily configured for different operating scenarios, providing both reliable and efficient communication. MIMO-UFMC-based transmissions, when used in combination with multiple-input multiple-output (MIMO) transmissions, have become widely accepted air interfaces that significantly improve spectral efficiency. This work presents a hybrid technique (HEDSLCT) as mathematical formulation of expressions that enable the analysis of ED performance based on the square-law combining (SLC) method in MIMO-UFMC systems, considering the future massive implementation of these systems in the fourth and fifth generation of mobile networks. The developed algorithms were used to conduct simulations for analyzing the performance of an ED process based on the SLC in MIMO-UFMC systems with varied numbers of transmit (Tx) and receive (Rx) communication branches. The results of these simulations enabled an evaluation of the ED performance. This paper presents an analysis of the effects of various factors, such as PU Tx power, false alarm probability, number of Tx and Rx MIMO branches, number of samples in ED process, and modulation techniques, on ED performance according to different signal-to-noise ratios. The obtained results of a comprehensive analysis showed that an appropriate selection of the evaluated factors could be used to improve the energy detection performance of multiple-input multiple-output ultra-wideband frequency-division multiplexing-based cognitive radio networks.