Analyses Hybrid Technique Detection Multiple Input Multiple Output 5G Waveforms

Author:

Algriree Waleed1,alsheakh H.2,Sulaiman Nasri1,Alghrairi Mokhalad3,Taher H4

Affiliation:

1. University Putra Malaysia

2. University of mustansiriyah

3. Imam Al kadhum College(IKC)

4. University of Thi-Qar

Abstract

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.

Publisher

Research Square Platform LLC

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3