Thirty years of machine learning: The road to Pareto-optimal wireless networks
Future wireless networks have a substantial potential in terms of supporting a broad range of
complex compelling applications both in military and civilian fields, where the users are able …
complex compelling applications both in military and civilian fields, where the users are able …
Machine learning paradigms for next-generation wireless networks
Next-generation wireless networks are expected to support extremely high data rates and
radically new applications, which require a new wireless radio technology paradigm. The …
radically new applications, which require a new wireless radio technology paradigm. The …
Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Machine learning techniques and a case study for intelligent wireless networks
With the widespread deployment of wireless technologies and IoT, 5G wireless networks will
support various communication connectivity and services for the huge number of wireless …
support various communication connectivity and services for the huge number of wireless …
Application of machine learning in wireless networks: Key techniques and open issues
As a key technique for enabling artificial intelligence, machine learning (ML) is capable of
solving complex problems without explicit programming. Motivated by its successful …
solving complex problems without explicit programming. Motivated by its successful …
Single and multi-agent deep reinforcement learning for AI-enabled wireless networks: A tutorial
Deep Reinforcement Learning (DRL) has recently witnessed significant advances that have
led to multiple successes in solving sequential decision-making problems in various …
led to multiple successes in solving sequential decision-making problems in various …
Machine learning for future wireless communications
FL Luo - 2020 - books.google.com
A comprehensive review to the theory, application and research of machine learning for
future wireless communications In one single volume, Machine Learning for Future Wireless …
future wireless communications In one single volume, Machine Learning for Future Wireless …
AI-enabled future wireless networks: Challenges, opportunities, and open issues
M Elsayed, M Erol-Kantarci - IEEE Vehicular Technology …, 2019 - ieeexplore.ieee.org
An expected plethora of demanding services and use cases mandates a revolutionary shift
in the way future wireless network resources are managed. Indeed, when application …
in the way future wireless network resources are managed. Indeed, when application …
Machine learning in beyond 5G/6G networks—State-of-the-art and future trends
Artificial Intelligence (AI) and especially Machine Learning (ML) can play a very important
role in realizing and optimizing 6G network applications. In this paper, we present a brief …
role in realizing and optimizing 6G network applications. In this paper, we present a brief …