The fifth-generation (5G) wireless network is quicker than the fourth-generation (4G) radio network and provides higher capacity, consistent coverage, and performance. In this blog, we discuss artificial intelligence and the 5G network.
5G Network
The low latency of 5G benefits real-time apps and enables various new IoT (Internet of Things) applications. Although the 5G network has the potential to alter many industries and apps, our focus in this essay is solely on AI-powered applications. The 5G network and AI can complement one other to provide end-users with considerably more reliable services.
5G and AI are both important enablers of future developments. The 5G network architecture meets AI processing needs and will enhance the number of AI-based applications in the future. AI applications, on the other hand, automate 5G network activities such as optimization, error detection, and so on.
How AI is enhancing the 5G network?
5G cellular businesses are focusing on combining AI with 5G capabilities in order to improve network performance and quality and provide more personalized services to their customers.
Here are a few examples of AI applications in the 5G network:
Identifying available channels: AI algorithms can increase connection quality by searching for available frequencies and providing intelligent awareness of RF activity, which was previously not possible.
Power consumption reduction: Intelligent network operation aids in the control of beamforming and the management of power consumption, particularly for small devices.
Prediction of network capacity: AI can assist in predicting 5G network capacity in order to optimize network utilization by apps. The application takes the available Quality-of-Service information and reacts to it based on the service being used, such as telephony or cloud computing.
AI-powered Digital Twin: A digital twin is a real-time simulation or virtual copy of a system that can be used to monitor the system’s activity.
A digital twin powered by AI opens up new possibilities, such as predicting accuracy utilizing acquired data for simulation. Such needs cannot be met by a rule-based digital twin. AI predicts potential future errors using real-time sensor data as well as past data.
To obtain real-time data for processing, AI systems require low latency data transmission. On Nvidia’s Omniverse platform, Ericsson simulates the full 5G wireless network using digital twin technology. A 5G digital twin is a novel technology for monitoring and validating network activities while improving performance and coverage.
How the 5G network is paving the way for artificial intelligence advancement?
MEC (Multi-access Edge Computing): AI applications typically necessitate greater processing power as well as rapid and secure communication, which is made possible by edge computing as part of the 5G network. AI applications can be distributed and deployed in a variety of locations, such as a car and infrastructure.
If there is a large demand for computational resources, the ideal solution is to run the AI application on the MEC server, which has computed and storage facilities. MEC servers are much faster than the cloud at communicating with other devices. “Connected Intelligence” enables AI applications and accelerates the deployment of AI in new future situations that were previously impossible. The fundamental characteristic of the next generation 6G cellular network as a platform, Connected Intelligence, can offer intelligence to any user, car, or gadget.
Autonomous driving development: Successful decision-making in autonomous cars is strongly reliant on sensor capability and redundancy. Cameras and radars, for example, provide crucial information on static and dynamic objects or obstacles on the road. In an open context environment, AI systems should be able to categorize any relevant object with sufficient accuracy.
Sensors should be installed in the vehicle as well as in the infrastructure to ensure safe autonomous driving. As a result, sensors require dependable and quick communication routes for the transmission of data and control commands. 5G is a viable and dependable alternative for enabling the execution of such AI algorithms on a large number of distributed and connected devices. Sensor data can be fused at a central location, such as a MEC server, and made available to all cars in this region or delivered on-demand.
Wireless Machine Learning: AI algorithms can launch a self-learning procedure thanks to the 5G network’s high capacity and low latency, as well as its dependable and secure communication capabilities. As all gadgets collect data and learn new data sets, AI applications and machine learning models will mature considerably faster. This approach can be extended to test or validate AI models.
AI-powered Virtual Reality/Augmented Reality: VR programs substitute your view and make you feel as if you are in a different location, whilst AR applications provide information about what you are looking at. The integration of AI and VR/AR technologies elevates them to a new level, adding new functionality such as text or facial recognition to estimate an object’s position.
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