RAN Optimization
AI RAN Alliance selects Alex Choi as Chairman
Backgrounder:
The AI RAN Alliance, formed earlier this year, is a groundbreaking collaboration aimed at revolutionizing the RAN industry. Partnering with tech giants, the goal is to transform traditional Radio Access Networks (RANs) into intelligent, self-optimizing systems using advanced AI technologies. Their website states:
Bringing together the technology industry leaders and academic institutions, the AI-RAN Alliance is dedicated to driving the enhancement of RAN performance and capability with AI. Moreover, we aim to optimize RAN asset utilization, and unlock new revenue streams. By pioneering AI-based innovations in RAN, we aspire to profitably propel the telecom industry towards 6G.
The alliance’s founding members include Amazon Web Services, Inc. (AWS), Arm, DeepSig Inc. (DeepSig), Telefonaktiebolaget LM Ericsson (Ericsson), Microsoft Corporation (Microsoft), Nokia, Northeastern University, NVIDIA, Samsung Electronics, SoftBank Corp. (SoftBank) and T-Mobile USA, Inc. (T-Mobile).
The group’s mission is to enhance mobile network efficiency, reduce power consumption, and retrofit existing infrastructure, setting the stage for unlocking new economic opportunities for telecom companies with AI, facilitated by 5G and 6G.
Image Courtesy of the AI RAN Alliance.
Purpose:
The AI RAN Alliance is dedicated to eliminating the inefficiencies of traditional RAN systems by embedding AI directly into network infrastructures. This shift will enable, for example, dynamic resource allocation, predictive maintenance, and proactive network management.
Industry Benefits:
Enhanced Network Efficiency: Real-time optimized bandwidth allocation and improved user experiences.
Economic Advantages: Cost savings from AI-driven automation and reduced energy consumption.
Innovative Revenue Opportunities: New services such as real-time AI Assistants on your mobile devices.
Key Focus Areas:
- AI for RAN
- AI on RAN (RAN for AI)
- AI and RAN
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New AI RAN Alliance Chairman:
On August 15, 2024, the AI RAN Alliance appointed Dr. Alex Jinsung Choi, Principal Fellow of SoftBank Corp.’s Research Institute of Advanced Technology as Chairman.
“The AI-RAN Alliance is set to transform telecommunications through AI-RAN advancements, increased efficiency, and new economic opportunities,” said Choi. “As Chair, I’m excited to lead this AI-RAN initiative, working with industry leaders to enhance mobile networks, reduce power consumption, and modernize infrastructure with 5G and 6G with AI/ML. Our goal is to drive societal progress through AI-RAN, transitioning from traditional to next-generation communications infrastructure.”
Satadal Bhattacharjee, Sr. Director of Marketing, Infrastructure BU, ARM, said, “We’re excited to collaborate with Choi, the Chair of the AI-RAN Alliance. Like Choi, we believe that AI will fundamentally change the way wireless services are deployed, fostering broad innovation and enhancing operational efficiency. We look forward to working with key industry leaders from silicon to software to fulfill the promise of ubiquitous AI and 6G.”
Jim Shea, Co-founder and CEO of DeepSig, said, “As a pioneer in AI-native communications together with his prior experience growing the O-RAN ALLIANCE, Choi will lead this important initiative that is shaping the future of intelligent radio access networks. DeepSig’s extensive AI/ML wireless expertise will play a key role in this exciting collaboration to leverage advanced technologies to help the industry unlock unprecedented network efficiency and accelerate innovation.”
Mathias Riback, VP & Head of Advanced Technology U.S., Ericsson, said, “I’m thrilled to welcome Dr. Choi as Chair of the AI-RAN Alliance. As a non-standardization organization, the Alliance can uniquely complement the work of existing SDOs by focusing on shaping innovative use cases that integrate AI with RAN. In addition to realizing benefits from AI in RAN implementations, it will be important to advance ‘AI on RAN’ use cases, where mobile networks play a critical role in enabling AI applications. Ericsson is fully committed to fostering a collaborative environment that unites all players in the evolving AI ecosystem to shape the future of telecom together.”
Shawn Hakl, VP of 5G Strategy, Microsoft, said, “At Microsoft, we recognize artificial intelligence (AI) as a pivotal technology of our era. We are excited to be a part of the AI-RAN Alliance and are particularly pleased to see Choi step into the role of Chair. Choi’s leadership will be key as we collaborate to leverage AI in optimizing RAN infrastructure investments and expanding the capabilities of RAN to introduce new AI-driven services for modern mobile applications.”
Ari Kynäslahti, Head of Strategy and Technology, Mobile Networks at Nokia commented, “Nokia is proud to be part of the AI-RAN Alliance and contribute towards integrating AI into radio access networks. The potential of AI to optimize networks, predict and resolve issues, and enhance performance and service quality is significant. As we embark on this transformative journey, collaboration is essential to harness our collective expertise. We are pleased to see Dr. Alex Choi appointed to this role, and look forward to him guiding our efforts to achieve these goals.”
Tommaso Melodia, William L. Smith Professor, Northeastern University, said, “We are pleased to have Choi as the Chair of the AI-RAN Alliance, leading our efforts to transform the industry. Choi has been a strong advocate for the evolution towards a more open, software-driven, and AI-integrated future. Under Choi’s leadership, the AI-RAN Alliance is set to fast-track the development of new services and use cases by leveraging openness, softwarization, and AI integration to enhance network performance, energy efficiency, spectrum sharing, and security, ultimately redefining the landscape of global communications.”
Soma Velayutham, GM, AI and Telecoms, NVIDIA, said, “The AI-RAN Alliance is a critical initiative for advancing the convergence of AI and 5G/6G technologies to drive innovation in mobile networks. The consortium’s new leadership will bring a fresh perspective and focus on delivering the next generation of connectivity.”
Dr. Ardavan Tehrani, Samsung Research, AI-RAN Alliance Board of Directors Vice Chair, said, “We are excited to have Dr. Alex Choi leading the AI-RAN Alliance as the Chair of the Board. The Alliance will play a pivotal role in fostering collaboration, driving innovation, and transforming future 6G networks utilizing AI. Under Dr. Choi’s leadership, the Alliance will strive to deliver substantial value to end users and operators through pioneering AI-based use cases and innovations.”
Ryuji Wakikawa, VP and Head of Research Institute of Advanced Technology, SoftBank Corp., said, “SoftBank is committed to realizing an AI-powered network infrastructure, and we strongly believe that Choi’s extensive background and expertise will be a great force in advancing AI-RAN technology and driving significant progress for the mobile industry in this AI era with lightning speed.”
John Saw, EVP and CTO, T-Mobile, said, “We are thrilled to have Alex Choi as Chair of the AI-RAN Alliance. AI is advancing at an unprecedented rate and with our 5G network advantage we have a unique opportunity to harness this momentum. By developing solutions that make the most of both RAN and AI on GPUs — and working alongside Choi and the top industry leaders within the Alliance — we believe there is potential for change that will revolutionize the industry.”
Dr. Akihiro Nakao, Professor, The University of Tokyo, said, “Dr. Alex Jinsung Choi’s appointment as Chair of the AI-RAN Alliance represents a pivotal step in advancing AI within the telecommunications sector. His leadership is expected to unite academic and industry efforts, nurturing the next wave of innovators who will drive the future of AI and telecommunications. This initiative will not only fast-track the adoption of AI across diverse applications but also foster international collaboration and set new standards for efficiency, energy management, resilience, and the development of AI-driven services that will reshape the telecommunications industry and benefit society worldwide.”
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References:
https://ai-ran.org/news/industry-leaders-in-ai-and-wireless-form-ai-ran-alliance/
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NEC’s new AI technology for robotics & RAN optimization designed to improve performance
NEC Corporation has developed AI technology for robotics that enables precise handling operations on unorganized and disorderly placed items. By predicting both the areas hidden by obstacles and the results of a robot’s actions, this technology makes it possible for robots to perform tasks that were previously performed manually, thereby contributing to the improvement of productivity and work-styles.
NEC has developed AI technology for robotics that consists of two technologies based on “World Models“:
“Spatiotemporal Prediction,” in which a robot precisely predicts the work environment and the results of its own actions from camera data, and
“Robot Motion Generation,” which automatically generates optimal and precise actions based on these predictions. According to NEC research, this is the world’s first technology of its kind to be applied to robot operations.
1. Autonomously executes precise actions in optimal sequences for items of various shapes and sizes:
The handling of objects performed manually at a work site are executed by a combination of various actions. For example, in packing items, people can instantly execute a combination of precise actions such as “placing and then pushing items” without hitting other objects or obstacles. In robot control that uses conventional technologies, however, actions such as “push” and “pull” are more difficult to execute with high precision than actions such as “pick up” and “place.” This is because slight differences in actions or shapes significantly influence how objects move in response to actions. In addition, as the number and types of actions to be considered increases, the combination and sequence of actions becomes more complex, which makes real-time planning a challenge.
This technology uses World Models to accurately predict the results of robot actions on objects of various shapes from video camera data, enabling robots to execute precise actions such as “push” and “pull.” Moreover, robots can autonomously and instantly execute combinations of multiple actions such as “place and push” and “pull and pick up” by generating the appropriate action sequence at real-time speed depending on the work environment.
2. Operates while predicting hidden and invisible items:
In a work environment where multiple items are closely arranged or disorderly piled up, people naturally predict the hidden areas and act accordingly, such as picking up items while avoiding interference with hidden objects. However, conventional recognition technology for robots has been difficult for practical use because it requires the preparation and learning of a large amount of teaching data showing the state of hidden objects in order to predict the hidden areas.
This new technology enables unsupervised learning that does not require labeling through the application of World Models and is able to efficiently learn prediction models of hidden object shapes. This enables robots to accurately predict a work environment from camera data and automatically generate optimal actions that do not collide with other objects or obstacles.
NEC will test this technology in logistics warehouses and other sites where much of the work is done manually by the end of 2024. By promoting social implementation of this technology in various industries with significant need for automation, NEC will contribute to improved productivity and work style reform.
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Separately, NEC has developed a RAN autonomous optimization technology that dynamically controls 5G Radio Access Networks (RAN) according to the status of each user terminal, dramatically improving the productivity of applications, such as the remote control of robots and vehicles. NEC will incorporate the technology into RAN Intelligent Controllers (RIC) and conduct demonstration tests using this technology by March 2025.
There is growing momentum to promote digital transformation (DX) by utilizing the latest technologies such as 5G, Artificial Intelligence (AI), and the Internet of Things (IoT) with the aim of resolving labor shortages and improving productivity.
When using these technologies for remote control of robots and vehicles, two-way communication consisting of status monitoring and control instructions for each robot/vehicle must be completed within a certain period of time.
However, if the communication latency exceeds the requirement, the operation is repeatedly suspended for safety reasons, resulting in a decrease in the operation rate and productivity. The communication delays, such as retransmission delays due to poor radio quality and queuing delays (*) due to congestion on the radio links, have been a barrier to the introduction of remote control systems.
Currently, stable communications environments have been achieved by installing high performance network equipment, providing sufficient frequency resources, increasing redundancy in coding and communication paths, and pre-configuration of RAN parameters according to the application. However, with these methods, it is difficult to widely support applications that are diversifying with the advancement of DX, and the time and cost required for implementation is also an issue.
About the RAN autonomous optimization technology:
The RAN autonomous optimization technology developed by NEC consists of AI that analyzes communication requirements and radio quality fluctuations on a per-user terminal basis, such as robots and vehicles, and AI that dynamically controls RAN parameters on a per-user terminal basis based on the results of that analysis. This AI learns from past operational records of robots and vehicles, and optimally controls RAN parameters such as modulation and coding scheme (target block error rate), radio resource allocation (resource block ratio), and maximum allowable delay (delay budget) while predicting the probability of exceeding communication latency requirements. Whereas in a typical 5G network, RAN parameters are fixed and set for the entire network, this technology dynamically controls them on a per-user terminal basis to improve application productivity.
Technology features are as follows.
1. Flexible support for a variety of applications
RAN parameters can be dynamically controlled according to the communication requirements of applications, enabling overall optimization even in environments where diverse applications are mixed.
2. O-RAN Alliance-compliant and easy to deploy
Since it can be mounted on RIC that are compliant with O-RAN Alliance standard specifications, it is easy to install or add to existing facilities.
3. Dramatic productivity gains are possible at industrial sites
Simulation results of applying this technology to a system that remotely controls multiple autonomous robots operating in factories or warehouses confirmed that the number of robot stoppages can be reduced by 98% or more compared to cases where this technology is not used.
NEC plans to incorporate the technology into RIC platforms compliant with the O-RAN Alliance standard specifications and conduct demonstration tests using this technology by March 2025.
NEC will exhibit this technology at MWC Barcelona 2024, the world’s largest mobile exhibition, which will be held from February 26 to February 29, 2024 at Fira Gran Via, Barcelona, Spain.
When using these technologies for remote control of robots and vehicles, two-way communication consisting of status monitoring and control instructions for each robot/vehicle must be completed within a certain period of time. However, if the communication latency exceeds the requirement, the operation is repeatedly suspended for safety reasons, resulting in a decrease in the operation rate and productivity. The communication delays, such as retransmission delays due to poor radio quality and queuing delays due to congestion on the radio links, have been a barrier to the introduction of remote control systems.