Conventionally, resource allocation is formulated as an optimization problem and solved
online with instantaneous scenario information. Since most resource allocation problems …

With the development of big data and artificial intelligence, cloud resource requests present
more complex features, such as being sudden, arriving in batches and being diverse, which …

Massive multiple-input-multiple-output (MIMO) systems support advanced applications with
high data rates, low latency, and high reliability in next-generation mobile networks …

This work advocates the use of deep learning to perform max-min and max-prod power
allocation in the downlink of Massive MIMO networks. More precisely, a deep neural network …

This paper purposes beam allocation problem for a massive MIMO system using Deep
Neural Network (DNN). We use supervised Machine Learning (ML) algorithm for Beam …

In this letter, a deep Q-learning network (DQN) based resource allocation (RA) scheme is
proposed for the massive multiple-input multiple-output (MIMO)-nonorthogonal multiple …

Heterogeneous cloud radio access networks (H-CRAN) is a new trend of SC that aims to
leverage the heterogeneous and cloud radio access networks advantages. Low power …

In this article, a joint task, spectrum, and transmit power allocation problem is investigated for
a wireless network in which the base stations (BSs) are equipped with mobile-edge …

Abstract Edge computing and IIoT (Industrial Internet of Things) are two representative
application scenarios in 5G (5th Generation) mobile communication technology network …

Cloud radio access network (C-RAN) aims to improve spectrum and energy efficiency of
wireless networks by migrating conventional distributed base station functionalities into a …