A survey of machine learning techniques applied to self-organizing cellular networks
In this paper, a survey of the literature of the past 15 years involving machine learning (ML)
algorithms applied to self-organizing cellular networks is performed. In order for future …
algorithms applied to self-organizing cellular networks is performed. In order for future …
Towards artificial intelligence enabled 6G: State of the art, challenges, and opportunities
S Zhang, D Zhu - Computer Networks, 2020 - Elsevier
Abstract 6G is expected to support the unprecedented Internet of everything scenarios with
extremely diverse and challenging requirements. To fulfill such diverse requirements …
extremely diverse and challenging requirements. To fulfill such diverse requirements …
Point-to-point communication in integrated satellite-aerial 6G networks: State-of-the-art and future challenges
This paper surveys the literature on point-to-point (P2P) links for integrated satellite-aerial
networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of …
networks, which are envisioned to be among the key enablers of the sixth-generation (6G) of …
An overview of reinforcement learning algorithms for handover management in 5G ultra-dense small cell networks
The fifth generation (5G) wireless technology emerged with marvelous effort to state, design,
deployment and standardize the upcoming wireless network generation. Artificial …
deployment and standardize the upcoming wireless network generation. Artificial …
Generative Adversarial Networks (GANs) in networking: A comprehensive survey & evaluation
Despite the recency of their conception, Generative Adversarial Networks (GANs) constitute
an extensively-researched machine learning sub-field for the creation of synthetic data …
an extensively-researched machine learning sub-field for the creation of synthetic data …
Load balancing for ultradense networks: A deep reinforcement learning-based approach
In this article, we propose a deep reinforcement learning (DRL)-based mobility load
balancing (MLB) algorithm along with a two-layer architecture to solve the large-scale load …
balancing (MLB) algorithm along with a two-layer architecture to solve the large-scale load …
Energy-efficient resource allocation in cognitive radio networks under cooperative multi-agent model-free reinforcement learning schemes
The most prominent challenge to the wireless community is to meet the demand for radio
resources. Cognitive Radio (CR) is envisioned as a potential solution that utilizes its …
resources. Cognitive Radio (CR) is envisioned as a potential solution that utilizes its …
Handover optimization scheme for LTE-Advance networks based on AHP-TOPSIS and Q-learning
T Goyal, S Kaushal - Computer Communications, 2019 - Elsevier
With the emblematical expansion of telecommunication networks, high data rate, and low
latency for User Equipment (UE) has arisen. 3GPP introduced Long Term Evolution (LTE) …
latency for User Equipment (UE) has arisen. 3GPP introduced Long Term Evolution (LTE) …
[HTML][HTML] Artificial intelligence linear regression model for mobility robustness optimization algorithm in 5G cellular networks
Ensuring reliable and stable communication links between User Equipment (UE) and
serving cellular networks during UE movement is one of the significant difficulties facing the …
serving cellular networks during UE movement is one of the significant difficulties facing the …
A survey of handover management in mobile HetNets: current challenges and future directions
With the rapid growth of data traffic and mobile devices, it is imperative to provide reliable
and stable services during mobility. Heterogeneous Networks (HetNets) and dense …
and stable services during mobility. Heterogeneous Networks (HetNets) and dense …