Power-Location Optimization for Cooperative Nomadic Relay Systems Using Machine Learning Approach

Power-Location Optimization for Cooperative Nomadic Relay Systems Using Machine Learning Approach

The exact expressions and simple tight lower bounds for end-to-end average symbol error rate (ASER) and outage probability (OP) are derived in amplify-and-forward (AF) source-relay-destination cooperative link, provided that source-destination path is correlated with the source-relay path. Afterward...

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Bibliographic Details
Main Authors: Hamid Amiriara, M. Reza Zahabi, Vahid Meghdadi
Format: Article
Language:English
Published: IEEE 2021-01-01
Series:IEEE Access
Subjects:
Correlated channel
Nakagami-<italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">m</italic> channels
cooperative communication systems
power allocation
relay location optimization
machine learning
Online Access:https://ieeexplore.ieee.org/document/9427525/

Internet

https://ieeexplore.ieee.org/document/9427525/

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