Quantum Machine Learning-Assisted Channel Capacity Analysis of L —branch SC Diversity Receiver in α — µ Fading and CCI Environment-Reference-Cited by-同舟云学术

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Quantum Machine Learning-Assisted Channel Capacity Analysis of L —branch SC Diversity Receiver in α — µ Fading and CCI Environment

Published:2022-11-04 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE Silchar Subsection Conference (SILCON)
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Author:

Krstic Dragana¹,Suljovic Suad²,Petrovic Nenad¹,Gurjar Devendra S.³,Yadav Suneel⁴,Rastogi Ashutosh⁴

Affiliation:

1. University of Nis,Faculty of Electronic Engineering,Nis,Serbia

2. The Academy of Technical Professional Studies Belgrade,Belgrade,Serbia

3. National Institute of Technology Silchar,Department of ECE,Assam,India

4. Indian Institute of Information Technology Allahabad,Department of ECE,Prayagraj,India

Funder

Ministry of Education

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10028779/10028780/10028953.pdf?arnumber=10028953

Reference33 articles.

1. Moment generating function of the generalized α - μ distribution with applications

2. The multivariate ? – µ distribution with arbitrary correlation and fading parameters;de souza;IEEE International Conference on Communications,2008

3. An experimentally validated fading model for THz wireless systems;papasotiriou;Scientific Reports,2021

4. The $\alpha$-$\mu$ Distribution: A Physical Fading Model for the Stacy Distribution

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1. Machine Learning Approach to QoS Adjustment Leveraging LCR in Mobile Networks Limited by Beaulieu-Xie Fading and Co-Channel Interference;2023 10th International Conference on Electrical, Electronic and Computing Engineering (IcETRAN);2023-06-05

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