Ayaz, Ferheen and Ayaz, Saqib (2020) Analysis of GFDM as a robust 5G communication technique in noisy environment. 2020 International Conference on Information Networking (ICOIN), Barcelona, Spain, 7 - 10 Jan 2020. Published in: 2020 International Conference on Information Networking (ICOIN). 811-813. IEEE ISSN 1976-7684 ISBN 9781728142005

PDF (© 2020 IEEE) - Accepted Version Download (617kB)

Abstract

One of the challenges of modulation techniques used in Fifth-Generation (5G) is their robustness in noisy environment. Conventional Orthogonal Frequency Division Multiplexing (OFDM) cannot be considered as a 5G waveform in its original form because of its certain limitations, such as performance degradation by impulsive noise (IN) and high peak to average power ratio (PAPR). Numerous modulation schemes proposed for 5G communications are able to overcome these drawbacks. Generalised Frequency Division Multiplexing (GFDM) is one of them. This paper analyses the performance of GFDM in presence of Additive White Gaussian Noise (AWGN), IN and Narrow Band Interference (NBI). It is found that GFDM is able to perform better than OFDM and Vector Orthogonal Frequency Division Multiplexing (VOFDM) in presence of noises, which can potentially be present in 5G applications. Simulation results show that GFDM achieve lower PAPR and Symbol Error Rate (SER) and an average of 10.73 dB and 4.73 dB gain in Signal to Noise Ratio (SNR) in presence of IN and combined IN and NBI respectively, as compared to OFDM and VOFDM.

Item Type:	Conference Proceedings
Additional Information:	© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works
Schools and Departments:	School of Engineering and Informatics > Engineering and Design
SWORD Depositor:	Mx Elements Account
Depositing User:	Mx Elements Account
Date Deposited:	12 Mar 2020 12:01
Last Modified:	18 Feb 2022 11:49
URI:	http://sro.sussex.ac.uk/id/eprint/90380

View download statistics for this item

📧 Request an update