Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/180158
Title: | Intelligent reflecting surfaces-assisted hybrid THz/RF system over generalized fading | Authors: | Premanand, Rithwik Vishwakarma, Narendra Singh, Ranjan Madhukumar, A. S. |
Keywords: | Engineering | Issue Date: | 2024 | Source: | Premanand, R., Vishwakarma, N., Singh, R. & Madhukumar, A. S. (2024). Intelligent reflecting surfaces-assisted hybrid THz/RF system over generalized fading. IEEE International Conference on Communications (ICC 2024), 5534-5539. https://dx.doi.org/10.1109/ICC51166.2024.10622184 | Project: | NRF-CRP23-2019-0005 FCP-NTU-RG-2022-014 |
Conference: | IEEE International Conference on Communications (ICC 2024) | Abstract: | Intelligent reflecting surface (IRS) technology is a promising solution for addressing the limitations of terahertz (THz) systems, including blockage effects and tremendous path loss. This paper investigates a novel IRS-assisted hybrid framework that seamlessly combines both THz and radio frequency (RF) technologies using a selection combining (SC) scheme, thereby enhancing system reliability. The study incorporates the deterministic and statistical properties of IRS in both RF and THz domains employing a sophisticated spatial scattering chan-nel model across generalized α - µ fading channels. Specifically, the exact closed-form expressions for the probability density function (PDF) and cumulative distribution function (CDF) of the output signal-to-noise ratio (SNR) are derived for both THz and RF links. From this, the outage probability and average symbol error rate (SER) are derived. Furthermore, asymptotic expressions are evaluated for outage and average SER, offering insights into diversity gain of the system. Simulation results reveal a significant enhancement in system performance and power savings for the proposed IRS-aided hybrid THz/RF system. These findings provide valuable insights into the practical implementation of IRS-assisted hybrid networks, contributing to the ongoing efforts for future wireless networks. | URI: | https://hdl.handle.net/10356/180158 | ISBN: | 978-1-7281-9054-9 | ISSN: | 1938-1883 | DOI: | 10.1109/ICC51166.2024.10622184 | DOI (Related Dataset): | 10.21979/N9/ZRTSHW | Schools: | College of Computing and Data Science | Rights: | © 2024 IEEE. All rights reserved. | Fulltext Permission: | none | Fulltext Availability: | No Fulltext |
Appears in Collections: | CCDS Conference Papers |
SCOPUSTM
Citations
50
1
Updated on Apr 30, 2025
Page view(s)
119
Updated on May 6, 2025
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.