Session 25: Open RAN | New Front Haul eCPRI, Mid Haul and Back Haul Connectivity and new requirement from pooja ran Watch Video

Preview(s):

Play Video:
(Note: The default playback of the video is HD VERSION. If your browser is buffering the video slowly, please play the REGULAR MP4 VERSION or Open The Video below for better experience. Thank you!)
⏲ Duration: 5:5
👁 View: 15K times
✓ Published: 03-Jun-2024
Open HD Video
Open MP4 Video
Download HD Video
Download MP4 Video
Description:
In this session, we delve into the crucial components of Open RAN: new front haul eCPRI, mid haul, and back haul connectivity. Understanding these elements is essential for optimizing network performance. We'll cover why new front haul eCPRI is needed, explain the roles of mid haul and back haul, and discuss the advancements required in Open RAN to meet the super-fast latency and throughput demands of modern networks. Join us to learn how these connectivity solutions enhance Open RAN deployments.<br/><br/>Welcome to Session 25! Today, we explore the essential parts of Open RAN connectivity: new front haul eCPRI, mid haul, and back haul. Understanding these components is key to enhancing network performance. We’ll discuss:<br/><br/>Why new front haul eCPRI is needed:<br/>* Enhanced Common Public Radio Interface (eCPRI) is an updated version of CPRI, essential for modern high-speed networks.<br/>* Benefits: Offers better bandwidth, reduced latency, and improved scalability compared to traditional CPRI.<br/><br/>What is mid haul:<br/>* Mid haul connects the centralized unit (CU) and distributed unit (DU) within the network.<br/>* Importance: Essential for efficient data transmission between the central and edge components, enabling flexibility in network deployment.<br/><br/>What is back haul:<br/>* Back haul refers to the connections between the distributed unit (DU) and the core network.<br/>* Role: Critical for carrying data from the edge of the network to the core, ensuring seamless communication and data flow.<br/><br/>Why these are needed in Open RAN:<br/>* These connectivity solutions enable the modular and scalable architecture of Open RAN.<br/>* Performance: They are crucial for achieving the desired network performance, including low latency and high throughput.<br/><br/>Advancements required in Open RAN:<br/>* Super-fast latency: To meet the demands of modern applications, Open RAN must continuously evolve to provide ultra-low latency.<br/>* High throughput: Ensuring high data transfer rates is necessary to support the growing data demands of users and applications.<br/><br/>By the end of this session, you'll have a clear understanding of how new front haul eCPRI, mid haul, and back haul connectivity work together to optimize Open RAN deployments, making them ready for the future of telecom networks.<br/><br/><br/>Subscribe to \

Share with your friends:

Whatsapp | Viber | Telegram | Line | SMS
Email | Twitter | Reddit | Tumblr | Pinterest

Related Videos

In this session, we delve into the crucial components of Open RAN: new front haul eCPRI, mid haul, and back haul connectivity. Understanding these elements is essential for optimizing network performance. We&#39;ll cover why new front haul eCPRI is needed, explain the roles of mid haul and back haul, and discuss the advancements required in Open RAN to meet the super-fast latency and throughput demands of modern networks. Join us to learn how these connectivity solutions enhance Open RAN deployments.&#60;br/&#62;&#60;br/&#62;Welcome to Session 25! Today, we explore the essential parts of Open RAN connectivity: new front haul eCPRI, mid haul, and back haul. Understanding these components is key to enhancing network performance. We’ll discuss:&#60;br/&#62;&#60;br/&#62;Why new front haul eCPRI is needed:&#60;br/&#62;* Enhanced Common Public Radio Interface (eCPRI) is an updated version of CPRI, essential for modern high-speed networks.&#60;br/&#62;* Benefits: Offers better bandwidth, reduced latency, and improved scalability compared to traditional CPRI.&#60;br/&#62;&#60;br/&#62;What is mid haul:&#60;br/&#62;* Mid haul connects the centralized unit (CU) and distributed unit (DU) within the network.&#60;br/&#62;* Importance: Essential for efficient data transmission between the central and edge components, enabling flexibility in network deployment.&#60;br/&#62;&#60;br/&#62;What is back haul:&#60;br/&#62;* Back haul refers to the connections between the distributed unit (DU) and the core network.&#60;br/&#62;* Role: Critical for carrying data from the edge of the network to the core, ensuring seamless communication and data flow.&#60;br/&#62;&#60;br/&#62;Why these are needed in Open RAN:&#60;br/&#62;* These connectivity solutions enable the modular and scalable architecture of Open RAN.&#60;br/&#62;* Performance: They are crucial for achieving the desired network performance, including low latency and high throughput.&#60;br/&#62;&#60;br/&#62;Advancements required in Open RAN:&#60;br/&#62;* Super-fast latency: To meet the demands of modern applications, Open RAN must continuously evolve to provide ultra-low latency.&#60;br/&#62;* High throughput: Ensuring high data transfer rates is necessary to support the growing data demands of users and applications.&#60;br/&#62;&#60;br/&#62;By the end of this session, you&#39;ll have a clear understanding of how new front haul eCPRI, mid haul, and back haul connectivity work together to optimize Open RAN deployments, making them ready for the future of telecom networks.&#60;br/&#62;&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 5:5 👁 15K
In this session, we&#39;ll provide a quick recap of key concepts in Open RAN (ORAN) and 5G technology. We&#39;ll cover the ORAN architecture, Virtualized Network Functions (VNF), Network Functions Virtualization (NFV) Management (NFVM), 5G nodes, and ORAN deployment strategies. This summary will help reinforce your understanding and prepare you for more advanced topics. Join us to revisit these crucial elements and see how they come together to shape the future of telecommunications.&#60;br/&#62;&#60;br/&#62;ORAN Architecture:&#60;br/&#62;* Overview: Modular and open architecture promoting interoperability and flexibility.&#60;br/&#62;* Benefits: Encourages innovation by allowing different vendors&#39; components to work together.&#60;br/&#62;&#60;br/&#62;Virtualized Network Functions (VNF):&#60;br/&#62;* Software implementations of network functions that run on virtualized infrastructure.&#60;br/&#62;* Advantages: Offers flexibility, scalability, and cost-efficiency in managing network services.&#60;br/&#62;&#60;br/&#62;Network Functions Virtualization (NFV) Management (NFVM):&#60;br/&#62;* Role: Manages the lifecycle of VNFs, including deployment, scaling, and orchestration.&#60;br/&#62;* Importance: Ensures efficient and dynamic network operations.&#60;br/&#62;&#60;br/&#62;5G Nodes:&#60;br/&#62;* Types: gNodeB (gNB) for 5G NR and ng-eNodeB (ng-eNB) for 4G evolved to support 5G.&#60;br/&#62;* Functionality: Provide radio access and connect users to the 5G core network.&#60;br/&#62;&#60;br/&#62;ORAN Deployment:&#60;br/&#62;* Approaches: Includes centralized, distributed, and hybrid deployment models.&#60;br/&#62;* Impact: Enhances network performance, reduces costs, and accelerates deployment times.&#60;br/&#62;&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 6:31 👁 25K
Welcome to Session 23! In this video, we&#39;ll dive into the world of Multi-Access Edge Computing (MEC) within the framework of Open RAN (ORAN). This beginner-friendly session breaks down the concepts, providing an easy-to-understand overview with real-world examples. We discuss the key benefits, potential challenges, and various use cases of MEC in ORAN. Learn why MEC is crucial for the future of mobile networks and how it can revolutionize connectivity and performance.&#60;br/&#62;&#60;br/&#62;Key Concepts :&#60;br/&#62;* Introduction to MEC and ORAN&#60;br/&#62;* Key advantages of MEC in ORAN&#60;br/&#62;* Common challenges and disadvantages&#60;br/&#62;* Practical use cases of MEC in ORAN&#60;br/&#62;* The importance of MEC in modern network architecture&#60;br/&#62;&#60;br/&#62;&#60;br/&#62;Welcome to Session 23!&#60;br/&#62;Hello everyone, and welcome to Session 23 of our series. Today, we will explore the fascinating topic of Multi-Access Edge Computing (MEC) in the context of Open RAN (ORAN). This session is designed for beginners, so we&#39;ll start with the basics and build up to more detailed insights.&#60;br/&#62;&#60;br/&#62;Introduction to MEC and ORAN&#60;br/&#62;Multi-Access Edge Computing (MEC) is an innovative technology that brings computation and data storage closer to the end user, significantly enhancing the performance and efficiency of applications and services. Open RAN (ORAN) is a new approach to building mobile networks using open and interoperable interfaces. By combining MEC with ORAN, we create a powerful synergy that transforms how data is processed and transmitted across networks.&#60;br/&#62;&#60;br/&#62;Key Advantages of MEC in ORAN&#60;br/&#62;* Reduced Latency: Processing data closer to the source drastically reduces latency, which is critical for applications such as online gaming, video streaming, and virtual reality.&#60;br/&#62;* Improved Network Efficiency: MEC offloads traffic from the core network, resulting in more efficient use of network resources and better overall performance.&#60;br/&#62;* Enhanced Security: Local data processing offers improved security and privacy controls, reducing the risk of data breaches.&#60;br/&#62;&#60;br/&#62;Common Challenges and Disadvantages&#60;br/&#62;* Complexity: Implementing MEC in an ORAN environment can be complex, requiring careful planning and integration.&#60;br/&#62;* Cost: Initial deployment costs can be high, but the long-term benefits often justify the investment.&#60;br/&#62;&#60;br/&#62;Practical Use Cases of MEC in ORAN&#60;br/&#62;* Smart Cities: MEC enables real-time data processing for traffic management, public safety, and environmental monitoring.&#60;br/&#62;* Healthcare: Supports advanced telemedicine applications by providing low-latency, high-reliability connections for remote surgeries and patient monitoring.&#60;br/&#62;* Industrial IoT: Facilitates real-time analytics and automation in manufacturing, improving efficiency and reducing downtime.&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 4:48 👁 15K
Hello and welcome to Session 16 of our Open RAN series! Today, we&#39;re diving into the fascinating world of machine learning and its impact on Open RAN networks. We&#39;ll be focusing on how machine learning can boost Open RAN performance, specifically in predicting throughput based on MCS coding schemes. This is a crucial aspect for optimizing network performance and resource allocation in Open RAN environments.&#60;br/&#62;&#60;br/&#62;1. Introduction to Machine Learning in Open RAN:&#60;br/&#62;Machine learning plays a pivotal role in enhancing Open RAN networks by enabling predictive capabilities, particularly in throughput optimization. By leveraging machine learning models, Open RAN can predict throughput based on the Modulation and Coding Scheme (MCS) coding scheme. Throughput prediction is critical for optimizing network performance and efficiently allocating resources, ensuring a seamless user experience.&#60;br/&#62;&#60;br/&#62;2. Developing Machine Learning Models for Throughput Prediction:&#60;br/&#62;Developing a machine learning model for throughput prediction in Open RAN requires several key considerations. Firstly, the model needs to be trained on a dataset that includes throughput data and corresponding MCS values. The model should be designed to handle the complex relationships between these variables and predict throughput accurately. Mathematical functions and algorithms such as regression and neural networks are commonly used for this purpose, as they can effectively capture the underlying patterns in the data.&#60;br/&#62;&#60;br/&#62;3. Deployment of Machine Learning Models in Open RAN:&#60;br/&#62;The deployment of machine learning models in Open RAN involves several steps. Once the model is trained and validated, it is deployed to the network where it operates in real-time. The model continuously monitors network conditions and predicts throughput based on incoming data. This information is then used to dynamically allocate network resources, optimizing performance and ensuring efficient operation.&#60;br/&#62;&#60;br/&#62;4. Training Data Acquisition Process:&#60;br/&#62;Acquiring training data for the machine learning model involves collecting throughput data and corresponding MCS values from the network. This data is then cleaned and formatted to remove any inconsistencies or errors. The cleaned data is used to train the model, ensuring that it can accurately predict throughput in various network conditions. The training data acquisition process is crucial as it directly impacts the accuracy and reliability of the machine learning model.&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 5:55 👁 10K
Welcome to Session 24! Today, we&#39;re diving into the world of Open RAN deployment in regional and edge clouds, focusing on the importance of cloud technology. As telecom moves to the cloud, it&#39;s important to understand how Open RAN fits into different cloud setups. Join us to discover the systems that work in these clouds and how they improve network performance and flexibility.&#60;br/&#62;&#60;br/&#62;Introduction to Cloudification and Its Importance in Open RAN&#60;br/&#62;Cloudification involves moving traditional telecom functions to cloud-based environments. This process is pivotal for modernizing network infrastructure, offering several advantages:&#60;br/&#62;&#60;br/&#62;* Scalability: Easily adjust network resources based on demand.&#60;br/&#62;* Flexibility: Quickly adapt and manage network functions.&#60;br/&#62;* Cost Efficiency: Reduce costs by utilizing shared cloud resources.&#60;br/&#62;* Innovation: Accelerate the deployment of new services and innovations.&#60;br/&#62;&#60;br/&#62;Open RAN and Cloudification&#60;br/&#62;Open RAN (Radio Access Network) promotes open and interoperable network components, which allows for more flexible and cost-effective network deployments. Cloudification supports Open RAN by providing the necessary infrastructure for these open interfaces and modular components.&#60;br/&#62;&#60;br/&#62;Deployment Scenarios for Open RAN&#60;br/&#62;* Regional Cloud Deployment:&#60;br/&#62;In regional cloud deployments, the baseband functions are hosted in regional data centers, providing a centralized approach.&#60;br/&#62;* Benefits: High resource utilization, simplified management, and enhanced performance due to centralized processing.&#60;br/&#62;* Systems Deployed:&#60;br/&#62;**Centralized Units (CU): Handle high-level processing tasks and control functions.&#60;br/&#62;**Core Network Functions: Manage data, signaling, and service delivery.&#60;br/&#62;Use Cases: Suitable for urban and densely populated areas where high capacity and centralized management are critical.&#60;br/&#62;&#60;br/&#62;Edge Cloud Deployment:&#60;br/&#62;In edge cloud deployments, baseband functions are distributed closer to the end-users at edge locations.&#60;br/&#62;* Benefits: Reduced latency and improved user experience by processing data near the source.&#60;br/&#62;* Systems Deployed:&#60;br/&#62;** Distributed Units (DU): Perform real-time processing and lower-layer functions.&#60;br/&#62;** User Plane Functions (UPF): Handle user data traffic locally.&#60;br/&#62;Use Cases: Ideal for suburban and rural areas where low latency and local processing are essential.&#60;br/&#62;&#60;br/&#62;Conclusion&#60;br/&#62;As telecom networks continue to evolve, integrating cloudification with Open RAN enables flexible and efficient network deployment. By understanding the deployment scenarios in regional and edge clouds, operators can strategically plan their network infrastructure to maximize performance and adaptability. Stay tuned for more insights into the future of telecom networks in our upcoming sessions.&#60;br/&#62;&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 4:13 👁 10K
Bollywood Celebs Support Rahul Gandhi: बॉलीवुड के कई सेलेब्स ऐसे है जो राहुल गांधी के समर्थक हैं. कई सेलेब्स ने भारत जोड़ो यात्रा के दौरान उनके साथ सड़क पर पैदल चलकर उन्हें अपना समर्थन दिया था. &#60;br/&#62; &#60;br/&#62;Bollywood Celebs Support Rahul Gandhi: There are many Bollywood celebs who are supporters of Rahul Gandhi. Many celebs had extended their support to him by walking on the road with him during Bharat Jodo Yatra. &#60;br/&#62; &#60;br/&#62; &#60;br/&#62; &#60;br/&#62; &#60;br/&#62;#ElectionResult2024#INDIAAlliance #congress #bjp &#60;br/&#62; &#60;br/&#62; &#60;br/&#62;&#60;br/&#62;~ED.120~PR.115~
⏲ 3:8 👁 145K
Welcome back to our journey through the world of Open RAN and machine learning. In this session, In this session, we&#39;ll explore the deployment of machine learning models in Open RAN networks, focusing on practical examples and deployment strategies.&#60;br/&#62;&#60;br/&#62;Deployment Example:&#60;br/&#62;Consider a scenario where an Open RAN operator wants to optimize resource allocation by predicting network congestion. They decide to deploy a machine learning model to predict congestion based on historical traffic data and network conditions.&#60;br/&#62;&#60;br/&#62;Deployment Steps:&#60;br/&#62;&#60;br/&#62;1. Data Collection and Preprocessing:&#60;br/&#62;The operator collects historical traffic data, including throughput, latency, and user traffic patterns.&#60;br/&#62;They preprocess the data to remove outliers and normalize features.&#60;br/&#62;&#60;br/&#62;2. Model Development:&#60;br/&#62;Data scientists develop a machine learning model, such as a regression model, to predict congestion based on the collected data.&#60;br/&#62;They use a development environment with libraries like TensorFlow or scikit-learn for model development.&#60;br/&#62;&#60;br/&#62;3. Offline Model Training and Validation (Loop 1):&#60;br/&#62;The model is trained on historical data using algorithms like linear regression or decision trees.&#60;br/&#62;Validation is done using a separate dataset to ensure the model&#39;s accuracy.&#60;br/&#62;&#60;br/&#62;4. Online Model Deployment and Monitoring (Loop 2):&#60;br/&#62;Once validated, the model is deployed in the network&#39;s edge servers or cloud infrastructure.&#60;br/&#62;Real-time network data, such as current traffic conditions, is fed into the model for predictions.&#60;br/&#62;Model performance is monitored using metrics like prediction accuracy and latency.&#60;br/&#62;&#60;br/&#62;5. Closed-Loop Automation (Loop 3):&#60;br/&#62;The model&#39;s predictions are used by the network&#39;s orchestration and automation tools to dynamically allocate resources.&#60;br/&#62;For example, if congestion is predicted in a certain area, the network can allocate additional resources or reroute traffic to avoid congestion.&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 4:9 👁 75K
Hi, Guys Welcome to&#92;
⏲ 26:44 👁 10K
Introduction:&#60;br/&#62;In this session, we&#39;ll introduce the RAN Intelligent Controller (RIC) and explore its role in enhancing network capabilities. We&#39;ll also discuss two examples highlighting the use of RIC in Open RAN scenarios.&#60;br/&#62;&#60;br/&#62;Introduction to RIC:&#60;br/&#62;The RAN Intelligent Controller (RIC) is a key component in Open RAN architecture, providing intelligent control and optimization capabilities to the RAN. RIC can be classified into Near Real-Time RIC (NRT-RIC) and Non-Real-Time RIC (Non-RT-RIC), each serving specific functions within the network.&#60;br/&#62;&#60;br/&#62;Example 1: RAN Slice for Enterprise Customer:&#60;br/&#62;We&#39;ll illustrate how NRT-RIC and Non-RT-RIC can facilitate the creation of RAN slices to cater to enterprise customers. For instance, consider an enterprise customer who has subscribed to services guaranteeing 50Mbps throughput for their users using various XAPPs (e.g., XRAN, XHSS, etc.). NRT-RIC can dynamically allocate resources and prioritize traffic in near real-time to meet the throughput requirements of these XAPPs, ensuring a reliable and high-performance connection for enterprise users. On the other hand, Non-RT-RIC can perform more complex and resource-intensive optimization tasks that do not require immediate action, such as long-term network planning and policy configuration.&#60;br/&#62;&#60;br/&#62;Example 2: Power Control using RIC Apps (RApps):&#60;br/&#62;We&#39;ll discuss another example focusing on power control using RIC Apps (RApps). RIC can leverage RApps to manage power usage in the RAN, optimizing energy consumption without compromising network performance. For instance, RIC can dynamically adjust transmit power levels based on traffic load and coverage requirements, leading to more efficient power utilization across the network.&#60;br/&#62;&#60;br/&#62;Conclusion:&#60;br/&#62;RIC plays a crucial role in enabling dynamic and intelligent control of the RAN, offering significant benefits in terms of performance optimization, resource allocation, and energy efficiency. These examples demonstrate the practical applications of NRT-RIC and Non-RT-RIC in addressing specific network requirements and enhancing overall network performance.&#60;br/&#62;&#60;br/&#62;RIC, NRT-RIC, Non-RT-RIC, RAN Slice, Enterprise Customer, Throughput, XAPPs, Power Control, RApps, Optimization, Resource Allocation, Energy Efficiency&#60;br/&#62;&#60;br/&#62;Subscribe to &#92;
⏲ 9:36 👁 5K

Related Video Searches

Back to Search

«Back to pooja ran Videos

Search pooja ran Desi Porn
Search pooja ran MMS Porn
Search pooja ran XXX Videos
Search pooja ran HD Videos
Search pooja ran XXX Posts
Search pooja ran Photos
Search pooja ran Leaks
Search pooja ran Web Series
Search pooja ran Pics
Search pooja ran VIP XXX

Search Videos

Recent Searches

indian desi girl sex out door jungle | xxx desi girl sexy bfhi movie nishiddho polliw porn maza netifixxx | rashmika mandan new sex | aunties dee | موهیول سکس | www xxx suntyadarsa sex pakistani 3gp videos | iv 83 net 17 nudeangalore kannada rape xxx banglay fat aunty xx video | maria smith aka bronwyn ball珠海双飞外围上门服务(qq微信284377164) vlg | 大庆大同区水磨会所(选人微信2920705321)约炮服务–上门spa服务–全套服务–桑拿特色服务 0321m | wwwjp | 卡塔尔fb广告海外流量(飞机tg:ppy883) qgi | ⏭查询微信519506303⏮怎么调取酒店监控证明是和我老婆去开房的⏭查询个人信息⏮ ibt | 乐虎国际娱乐官方网网页版(关于乐虎国际娱乐官方网网页版的简介) 【网hk8989点com】 博天堂下载(关于博天堂的简介)9cyw9cyw 【网hk8989。com】 吉祥彩票官网登陆(关于吉祥彩票官网登陆的简介)cfrms5wt xjp | 万宁大学生伴游女微信嶶信6335317选妹网址ym599 com万宁足疗足浴指压按摩 万宁哪里有少妇全套服务 hgi | neufilks web series | katrina kahf xxx com move | school dress girls | 新干县约小姐一条龙服务123看妹q▷512506669125新干县约小姐包夜服务▷新干县找小妹约上门服务 zotsd | sister suck little brother | naked solo | andrea bulgaria | xxx kajal aggarwail wife sister xxx vro xxxx | indian old aunty xxx video 2015 উংলঙ্গ বাংলা নায়িকা মৌসুমির চুদাচুদি sasural simar ka nude all | www nora fatehi x | best hot open jatra sex song dance | sanam khan porn image from qubool haiwestindies xxx videos school 16 age girl sex bad wexxx | maduri bf com rape porn 3gp porn com | indonesia xxx porno medan asikallu aunty hot | sani dawani mal xxx | annapurna sex puku actress | fitri fay hot bigo | germany sex movie | 兴奋剂购买➕网址:ge380 com➕火狐狸购买➕网址:ge380 com➕fpw | সাদিয়া sex | 谷歌优化🍉(电报e10838)google留痕 kcl | plus size masturbating | sex badu | 外围第二季♛㍧☑【免费版jusege9 com】☦️㋇☓•hz8l | gz6led51kue | মা ও শিশুর সেক্স ভিডিও | 上海凯世精品酒店品茶喝茶资源预约(v电➡️17155201234)【沪上老李】上海最靠谱的外围模特经纪sq4ec9 | lankawe school kellange xxx photo | malayalam bhabi mms leaked |
<