Channel Capacity Enhancement in Dual Branch MRC under Extreme Fading Using Quantum Computing

We have investigated the potential of channel capacity and signal integrity enhancement in dual branch MRC systems even under extreme fading through classical and quantum computing. We have used the classical algorithm to gauge the performance of the quantum algorithm, including QAOA and QEC. Our simulation results show that quantum-assisted MRC work optimally by providing superior SNR and BER. Quantum algorithms not only maximizes the effective channel capacity but also minimizes end-to-end system latency and number of error rate more efficiently. The addition of Quantum Machine Learning for the dynamic parameter setting in real-time has demonstrated that it may be possible to combat severe fading effects. To the best of our knowledge, this paper laid the cornerstone to explore more opportunities in implementing quantum-enabled techniques for advanced telecommunication system development to realize more robust and efficient technologies.

Authors

Institutions

Publication Details

Published
2024-09-27
DOI
https://doi.org/10.1109/tensymp61132.2024.10752246
Citations
4
Primary Topic
Optical Network Technologies
Type
article
Field-Weighted Citation Impact
0.83
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Channel Capacity Enhancement in Dual Branch MRC under Extreme Fading Using Quantum Computing

Mridul Gupta, Abhay Upadhyay, Deepak Upadhyay, Kunj Bihari Sharma
4 citations
Optical Network Technologies
0.83
article

Channel Capacity Enhancement in Dual Branch MRC under Extreme Fading Using Quantum Computing

Mridul Gupta, Abhay Upadhyay, Deepak Upadhyay, Kunj Bihari Sharma
article en
4 citations

Abstract

We have investigated the potential of channel capacity and signal integrity enhancement in dual branch MRC systems even under extreme fading through classical and quantum computing. We have used the classical algorithm to gauge the performance of the quantum algorithm, including QAOA and QEC. Our simulation results show that quantum-assisted MRC work optimally by providing superior SNR and BER. Quantum algorithms not only maximizes the effective channel capacity but also minimizes end-to-end system latency and number of error rate more efficiently. The addition of Quantum Machine Learning for the dynamic parameter setting in real-time has demonstrated that it may be possible to combat severe fading effects. To the best of our knowledge, this paper laid the cornerstone to explore more opportunities in implementing quantum-enabled techniques for advanced telecommunication system development to realize more robust and efficient technologies.

Graphic Era University (IN)
Affordable and clean energy
Openalex Percentile: Top 26%
Optical Network Technologies
0.83
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.