Survey on Machine Learning in 5G

Abstract

The core of next generation 5G wireless network is heterogeneous network. The upcoming 5G heterogeneous network cannot be fulfilled until Artificial Intelligence is deployed in the network. The existing traditional 4G technology approaches are centrally managed and reactive conception-based network which needs additional hardware for every update and when there is a demand for the resources in the network. 5G helps in giving solution to the problem of 4G network using prediction and traffic learning to increase performance and bandwidth. Heterogeneous network provides more desirable Quality of Service (QOS) and explores the resources of the network explicitly. The assortment of heterogeneous network brings difficulty in traffic control of the network. The problem in heterogeneous network is network traffic which cannot be controlled and managed due to different protocols and data transfer rate. To solve the problem in heterogeneous network advanced techniques like Artificial Intelligence (AI), Machine Learning (ML) and Deep Learning (DL) are employed in 5G Network which are self pro-active, predictive and adaptive. In this paper we discuss about above mentioned advanced techniques that are deployed in 5G to reduce traffic in a network which increases efficiency of the network.