The rest of the chapter is built by giving a short overview on AI and ML definitions, historic and (sub-) classes in second section. In this chapter, we describe the role and the integration method of AI and different ML approaches as core part of AI in the next generation mobile networks. For example, AI/ML are crucial for massive MIMO to identify dynamic change and forecast the user distribution by analyzing historical data, dynamically optimize the weights of antenna elements using the historical data or to improve the coverage in a multi-cell scenario considering the inter-site interference between multiple 5G massive MIMO cell sites, etc. This is true for each layer of the system and each level of the network. The adoption of Artificial Intelligence (AI), and Machine Learning (ML) approaches as core part of AI, is crucial to forecast the evolution of the environment and users/services behavior/demand to build a pro-actively and efficiently (self-) optimizing and (self-) updating networks. Network operators are also forced to consider a higher level of intelligence in their networks, in order to deeply and accurately learn the operating environment and users behaviors and needs. Facilitating such partnerships may act as catalyst for the deployment of 5G networks, considering the large investments for mobile network operators (MNOs) in capital expenditure CAPEX and operational expenditure OPEX are still not being followed by significant revenue increase. Furthermore, the network operators have to establish more partnerships on multiple layers for sharing of the 5G infrastructure through network sharing relationship among different mobile operators, delivery of Infrastructure as a Service, Platform as a Service or Network as a Service by assets providers. The main challenge is to be ready to support services for customers in completely different vertical markets/industries, like e-health, Internet-of-Vehicles (IoV), Industry 4.0, smart grids, etc. This should allow the network operators to support current and new more demanding future services.
ARTIFICIAL INTELLIGENCE IN 5G TECHNOLOGY SOFTWARE
Furthermore, 5G is planned to include a high level of flexibility to optimize the network utilization by integrating software defined networking (SDN) and network function virtualization (NFV) technologies. The 5G systems solved the major problems related to the capacity through use of new radio interface, massive MIMO, beamforming, high modulation orders, etc. Furthermore, mobile networks are facing other new services with extremely demand of higher reliability and almost zero-latency performance, like vehicle communications or Internet-of-Vehicles (IoV). However, new bandwidth-hungry services have been developed in unprecedented way, reaching capacities up to 1 Gbps, such as virtual reality (VR), augmented reality (AR), etc. This was possible mainly through very strong physical layer, based on orthogonal frequency division multiplexing (OFDM) and multiple input multiple output (MIMO) among others, and flexible network architecture. The massive deployment of LTE (Long Term Evolution) or 4G mobile network has solved one of the major challenges of wireless communications, which is high capacities, to build real broadband mobile Internet. Some practical use cases of AI/ML in network life cycle are discussed. In this chapter, we describe the role of artificial intelligence and machine learning in 5G and beyond, to build cost-effective and adaptable performing next generation mobile network. It is also important to forecast their evolution to build a pro-actively and efficiently (self-) updatable network. However, network operators are forced to consider a higher level of intelligence in their networks, in order to deeply and accurately learn the operating environment and users behaviors and needs. In addition, the adoption of software defend networks (SDN) and network function virtualization (NFV) has added a higher degree of flexibility allowing the operators to support very demanding services from different vertical markets. Using new radio interface based on massive MIMO, 5G has overcame some of these challenges. However, the bandwidth hungry services have been developed in unprecedented way, such as virtual reality (VR), augmented reality (AR), etc. This was possible mainly through very strong physical layer and flexible network architecture. The deployment of 4G/LTE (Long Term Evolution) mobile network has solved the major challenge of high capacities, to build real broadband mobile Internet.
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