Generic placeholder image

International Journal of Sensors, Wireless Communications and Control

Editor-in-Chief

ISSN (Print): 2210-3279
ISSN (Online): 2210-3287

Research Article

Non-orthogonal Multiple Access (NOMA) Channel Estimation for Mobile & PLC-VLC Based Broadband Communication System

In Press, (this is not the final "Version of Record"). Available online 19 July, 2024
Author(s): Manidipa Sarkar, Ankit Nayak, Sarita Nanda* and Suprava Patnaik
Published on: 19 July, 2024

DOI: 10.2174/0122103279310677240606101233

Price: $95

Abstract

Background: The paper focuses on enhancing the performance of 5G wireless mobile communication systems. Furthermore, it addresses the increasing demand for high data rates, improved channel capacity, and spectrum efficiency outlined by the 3rd Generation Partnership Project (3GPP) protocol.

Objective: To develop an innovative Non-Orthogonal Multiple Access (NOMA)-based channel estimation (CE) model aimed at improving the performance of 5G wireless mobile communication systems.

Methods: A proportionate recursive least squares (PRLS) algorithm is utilized for estimating the characteristics of practical Rayleigh fading channels. The applicability of the PRLS algorithm is investigated in Lambertian channels for indoor broadband communication systems such as power line communication (PLC) and visual light communication (VLC) systems.

Results: The assessment of evaluation metrics, including mean square error (MSE), bit error rate (BER), spectral efficiency (SE), energy efficiency (EE), capacity, and data rate, have been analysed. Faster convergence and higher accuracy compared to existing state-of-the-art approaches have been demonstrated.

Conclusion: The NOMA-based channel estimation model presents significant promise in enhancing the performance of 5G wireless communication systems. The demands for higher data rates and improved spectral efficiency as per 3GPP standards have been addressed.


Rights & Permissions Print Cite
© 2025 Bentham Science Publishers | Privacy Policy