Intelligent Resource Allocation in LoRaWAN Using Machine Learning Techniques-Reference-Cited by-同舟云学术

Intelligent Resource Allocation in LoRaWAN Using Machine Learning Techniques

Published:2023 Issue: Volume:11 Page:10092-10106
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Minhaj Syed Usama¹,Mahmood Aamir²^ORCID,Abedin Sarder Fakhrul²^ORCID,Hassan Syed Ali³^ORCID,Bhatti Muhammad Talha³,Ali Syed Haider³^ORCID,Gidlund Mikael²^ORCID

Affiliation:

1. Department of Electrical Engineering and Information Technology, Technical University of Munich, Munich, Bavaria, Germany

2. Department of Computer and Electrical Engineering, Mid Sweden University, Sundsvall, Sweden

3. School of Electrical Engineering and Computer Science (SEECS), National University of Sciences and Technology (NUST), Islamabad, Pakistan

Funder

Knowledge Foundation Sweden (KKS) Research Profile Next Generation Industrial IoT (NIIT) and WICOM

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/10005208/10026819.pdf?arnumber=10026819

Reference44 articles.

1. Synchronous LoRa Communication by Exploiting Large-Area Out-of-Band Synchronization

2. Energy Efficiency Optimization in LoRa Networks—A Deep Learning Approach

3. Range and coexistence analysis of long range unlicensed communication

4. Smart Measurement Systems Exploiting Adaptive LoRaWAN Under Power Consumption Constraints: a RL Approach

5. Interference Modelling in a Multi-Cell LoRa System

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