_session-13-leveraging-ai-and-machine-learning-in-open-ran-124-revolutionizing-networks.jpg "Session 13: Leveraging AI and Machine Learning in Open RAN | Revolutionizing Networks from odu guyaa haraa 18 Video Screenshot Preview")
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⏲ Duration: 4:15
👁 View: 25K times
✓ Published: 02-Apr-2024
👁 View: 25K times
✓ Published: 02-Apr-2024
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Welcome to Session 13 of our Open RAN series! In this session, we'll explore the integration of Artificial Intelligence (AI) and Machine Learning (ML) in Open RAN. These technologies play a crucial role in designing intelligent systems that enhance the overall ecosystem of Open RAN.<br/><br/>Artificial Intelligence and Machine Learning<br/>Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. Machine Learning (ML) is a subset of AI that allows machines to learn from data without being explicitly programmed. These technologies can revolutionize Open RAN by enabling intelligent decision-making, predictive maintenance, and network optimization.<br/><br/><br/>Application of Machine Learning in Open RAN<br/>Machine Learning algorithms use mathematical functions to analyze data and make predictions or decisions based on that analysis. In Open RAN, ML can be applied to various areas such as network optimization, predictive maintenance, and intelligent resource allocation. ML algorithms can analyze network traffic patterns, predict equipment failures, and optimize network performance, leading to improved efficiency and reliability.<br/><br/><br/>Join us as we explore the potential of AI and Machine Learning in Open RAN. Don't forget to subscribe to the \
Welcome to Session 13 of our Open RAN series! In this session, we'll explore the integration of Artificial Intelligence (AI) and Machine Learning (ML) in Open RAN. These technologies play a crucial role in designing intelligent systems that enhance the overall ecosystem of Open RAN.<br/><br/>Artificial Intelligence and Machine Learning<br/>Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and learn like humans. Machine Learning (ML) is a subset of AI that allows machines to learn from data without being explicitly programmed. These technologies can revolutionize Open RAN by enabling intelligent decision-making, predictive maintenance, and network optimization.<br/><br/><br/>Application of Machine Learning in Open RAN<br/>Machine Learning algorithms use mathematical functions to analyze data and make predictions or decisions based on that analysis. In Open RAN, ML can be applied to various areas such as network optimization, predictive maintenance, and intelligent resource allocation. ML algorithms can analyze network traffic patterns, predict equipment failures, and optimize network performance, leading to improved efficiency and reliability.<br/><br/><br/>Join us as we explore the potential of AI and Machine Learning in Open RAN. Don't forget to subscribe to the \
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_session-11-open-ran-protocol-stack-124-pdcp-protocol-and-sdap-layer.webp "Welcome to Session 11 of our Open RAN series! In this session, we'll dive into Layer 2 functionalities, focusing on key protocols and their roles in Open RAN networks.<br/><br/>PDCP Protocol Layer: The PDCP layer, or Packet Data Convergence Protocol layer, plays a crucial role in Open RAN environments by ensuring reliable data transmission. It is responsible for various functions such as header compression, ciphering, and integrity protection. PDCP sits above the RLC (Radio Link Control) layer and below the RRC (Radio Resource Control) layer in the protocol stack. Its primary role is to provide an error-free and secure transmission path for user data.<br/><br/>PDCP Functionalities in Dual Connectivity Mode: Dual connectivity mode in wireless networks allows a device to connect to multiple cells simultaneously, enhancing data rates and reliability. In this mode, the PDCP layer manages the data streams from both connected cells, ensuring seamless transmission and reception of data. This involves coordination between the PDCP entities in the device and the network to optimize data delivery. PDCP ensures that data from different cells is properly aggregated and delivered to the higher layers of the protocol stack.<br/><br/>SDAP Protocol: The Service Data Adaptation Protocol (SDAP) is a protocol used in Open RAN to adapt user-plane data for transmission over the network. SDAP is responsible for mapping different types of user-plane data flows to specific QoS (Quality of Service) requirements and network resources. It ensures that user data is transmitted efficiently and in accordance with the network's capabilities and policies. SDAP also provides mechanisms for congestion control and flow management, ensuring smooth operation of the network under varying traffic conditions.<br/><br/><br/>Join us as we unravel the complexities of Layer 2 functionalities in Open RAN, providing valuable insights into the network's operation. Don't forget to subscribe to the \")
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