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Leveraging Machine Learning and Artificial Intelligence for 5G

The heterogenous nature of future wireless networks comprising of multiple access networks, frequency bands and cells - all with overlapping coverage areas - presents wireless operators with network planning and deployment challenges.

ML and AI can assist in finding the best beam by considering the instantaneous values updated at each UE measurement of the parameters mentioned below: Once the UE identifies the best beam, it can start the random-access procedure to connect to the beam using timing and angular information.

Massive simply refers to the large number of antennas (32 or more logical antenna ports) in the base station antenna array. Massive MIMO enhances user experience by significantly increasing throughput, network capacity and coverage while reducing interference by: The weights for antenna elements for a massive MIMO 5G cell site are critical for maximizing the beamforming effect.

ML and AI can collect real time information for multidimensional analysis and construct a panoramic data map of each network slice based on: Different aspects where ML and AI can be leveraged include: With future heterogenous wireless networks implemented with varied technologies addressing different use cases providing connectivity to millions of users simultaneously requiring customization per slice and per service, involving large amounts of KPIs to maintain, ML and AI will be an essential and required methodology to be adopted by wireless operators in near future.

All of them address low latency use cases where the sensing and processing of data is time sensitive. These use cases include self-driving autonomous vehicles, time-critical industry automation and remote healthcare. 5G offers ultra-reliable low latency which is 10 times faster than 4G. However, to achieve even lower latencies, to enable event-driven analysis, real-time processing and decision making, there is a need for a paradigm shift from the current centralized and virtualized cloud-based AI towards a distributed AI architecture where the decision-making intelligence is closer to the edge of 5G networks.

The 5G mm-wave small cells require deep dense fiber networks and the cable industry is ideally placed to backhaul these small cells because of its already laid out fiber infrastructure which penetrates deep into the access network close to the end-user premises.

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