AI in Networks Market
SKT-Samsung Electronics to Optimize 5G Base Station Performance using AI
SK Telecom (SKT) has partnered with Samsung Electronics to use AI to improve the performance of its 5G base stations in order to upgrade its wireless network. Specifically, they will use AI-based 5G base station quality optimization technology (AI-RAN Parameter Recommender) to commercial 5G networks.
The two companies have been working throughout the year to learn from past mobile network operation experiences using AI and deep learning, and recently completed the development of technology that automatically recommends optimal parameters for each base station environment. When applied to SKT’s commercial network, the new technology was able to bring out the potential performance of 5G base stations and improve the customer experience.
Mobile base stations are affected by different wireless environments depending on their geographical location and surrounding facilities. For the same reason, there can be significant differences in the quality of 5G mobile communication services in different areas using the same standard equipment.
Accordingly, SKT utilized deep learning, which analyzes and learns the correlation between statistical data accumulated in existing wireless networks and AI operating parameters, to predict various wireless environments and service characteristics and successfully automatically derive optimal parameters for improving perceived quality.
Samsung Electronics’ ‘Network Parameter Optimization AI Model’ used in this demonstration improves the efficiency of resources invested in optimizing the wireless network environment and performance, and enables optimal management of mobile communication networks extensively organized in cluster units.
The two companies are conducting additional learning and verification by diversifying the parameters applied to the optimized AI model and expanding the application to subways where traffic patterns change frequently.
SKT is pursuing advancements in the method of improving quality by automatically adjusting the output of base station radio waves or resetting the range of radio retransmission allowance when radio signals are weak or data transmission errors occur due to interference.
In addition, we plan to continuously improve the perfection of the technology by expanding the scope of targets that can be optimized with AI, such as parameters related to future beamforming*, and developing real-time application functions.
* Beamforming: A technology that focuses the signal received through the antenna toward a specific receiving device to transmit and receive the signal strongly.
SKT is expanding the application of AI technology to various areas of the telecommunications network, including ‘Telco Edge AI’, network power saving, spam blocking, and operation automation, including this base station quality improvement. In particular, AI-based network power saving technology was recently selected as an excellent technology at the world-renowned ‘Network X Award 2024’.
Ryu Tak-ki, head of SK Telecom’s infrastructure technology division, said, “This is a meaningful achievement that has confirmed that the potential performance of individual base stations can be maximized by incorporating AI,” and emphasized, “We will accelerate the evolution into an AI-Native Network that provides differentiated customer experiences through the convergence of telecommunications and AI technologies.”
“AI is a key technology for innovation in various industrial fields, and it is also playing a decisive role in the evolution to next-generation networks,” said Choi Sung-hyun, head of the advanced development team at Samsung Electronics’ network business division. “Samsung Electronics will continue to take the lead in developing intelligent and automated technologies for AI-based next-generation networks.”
SK Telecom and Samsung Electronics researchers discussing verification of AI-based 5G base station quality optimization technology.
SK Telecom and Samsung Electronics researchers discussing verification of AI-based 5G base station quality optimization technology.
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SKT said it is expanding the use of AI to various areas of its communications network, such as “Telco Edge AI,” network power reduction, spam blocking and operation automation, including basestation quality improvement.
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References:
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Markets and Markets: Global AI in Networks market worth $10.9 billion in 2024; projected to reach $46.8 billion by 2029
According to research firm Markets and Markets, the global AI in Networks market is expected to be valued at USD 10.9 billion in 2024 and is projected to reach USD 46.8 billion by 2029 and grow at a CAGR of 33.8% from 2024 to 2029. AI in networks market is experiencing high growth driven by increasing adoption of 5G technology, edge computing, IoT connected devices, and expansion of smart cities. Increasing deployment of 5G networks has led to the vast amount of network data, generated by high bandwidth application such as video streaming and online gaming, driving network operators to integrate AI driven solutions to manage network data and allocate resources to reduce network congestion. Network operators are also integrating AI driven solutions to automate network operations and predictive maintenance, to reduce human dependency and errors, leading to efficient network management.
Network operators invest heavily in developing AI-driven solutions to manage and optimize network traffic. AI in networks allows operators to efficiently perform network management tasks such as traffic routing, resource allocation, and network security. As the 5G technology advances, the demand for cybersecurity solutions will also rise, driving the AI in networks market.
Constraint: Data privacy and security concerns in AI in networks
Integration of artificial intelligence technology in the networking leads to various risks affiliated with collecting, storing, and transmitting network traffic data. AI driven network collect users and network operations data information, creating a high risk environment of privacy breaches, due to the rising cyberthreats. These cyberattacks may lead to unauthorized access to network and user data, disrupting network operations. Additionally, data generated by connected and Iot devices such as smartphones, smart home systems, surveillance system is collected by network, leads to concerns regarding unauthorized surveillance and cyberattacks.
Opportunity: Increasing prevalence of smart city initiatives
Rapid urbanization has led to the exapsnion of smart cities globally. Countries around the world are investing heavily towards smart infrastructure by integrating advanced technologies such as artificial intelligence (AI). For instance, smart city ecosystem consist of various sensors and connected and IoT devices, and to ensure efficient transmission and processing of data generated by these sensor and devices. AI driven network solutions play a vital role in collecting and processing of data, identifying anomalies and equipment failure based on present and historical data, helping network operator to schedule maintenance in advance and reduce downtime.
Challenge: Rapid change in the technology landscape
As the technology landscape evolves rapidly, AI presents a major challenge in the network market. As new technologies appear and current technology evolves, companies in the ecosystem must continuously invest in the research and development of changing market demand and advancements. Additionally, intense competition in the market and pressure to offer innovative solutions further restrict companies from maintaining market leadership. Companies’ negligence in identifying the technological shift can result in a decline in market share and revenue.
AI in networks market in North America will hold the highest market share during the forecast period.
The AI in networks market for North America is expected to hold the highest market share during the forecast period. This growth is attributed to the presence of leading AI and network technology companies in the region. These companies are investing heavily towards the advancement of technologies such as AI, 5G, edge computing, due to the high internet penetration rate in the region. The demand for high bandwidth network application such as video streaming and online gaming also on the rise, driving the investments and innovations towards AI driven solutions in network management.
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References:
https://www.marketsandmarkets.com/Market-Reports/ai-in-networks-market-131514910.html
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