可编程网络

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爱立信破解运营商“管道化”困局:可编程网络与AI双轮驱动
Huan Qiu Wang· 2025-06-03 12:02
Core Viewpoint - The global telecommunications industry is facing a "growth without revenue" bottleneck, where the increase in network traffic does not translate into corresponding revenue growth, leading to a "growth reduction" phenomenon [1][3]. Group 1: Industry Challenges - The traditional network service model is homogenized, failing to meet diverse market demands, resulting in a lack of differentiation between high-value and ordinary services [1]. - Operators are experiencing a "pipeline" dilemma, where the expansion of 5G networks does not yield proportional income increases [1]. Group 2: Differentiated Connectivity - "Differentiated connectivity" has become a consensus in the industry, focusing on using technology to identify the value of different services and providing customized network guarantees for high-priority applications [3]. - Singapore Telecommunications (Singtel) exemplifies this approach by offering tiered service packages based on user needs, transforming operators from mere traffic providers to "service value definers" [3]. Group 3: Programmable Networks and AI Integration - Ericsson views programmable networks as a core development goal for 5G-A, enabling dynamic network configuration based on business needs through software-defined networking (SDN) and network function virtualization (NFV) [5]. - The integration of AI is reshaping network management, transitioning from passive to proactive management, with AI acting as a "network brain" for autonomous decision-making [5][7]. Group 4: Ecosystem Development - Ericsson is building an open ecosystem to attract third-party developers, creating a "network as a service" economic model, with a RAN ecosystem comprising 56 members [8]. - The acquisition of Vonage and the establishment of Aduna aim to create a CPaaS ecosystem, addressing fragmentation in network capability and enhancing collaboration with developers [8]. Group 5: Future Outlook - Despite the commercial launch of 5G-A, challenges remain, including deployment strategy delays in some regions and low penetration rates of new terminals [9]. - Ericsson proposes a dual-track development strategy to enhance 5G-A capabilities while promoting end-to-end differentiated services, aiming to redefine the telecommunications industry's revenue model and digital infrastructure [9].
对话爱立信高管:5G走向差异化服务,AI融合提升服务效率
Bei Ke Cai Jing· 2025-05-29 13:40
Group 1 - The communication industry is undergoing a critical transformation, with 5G requiring differentiation and platformization for commercial growth, while AI is driving networks towards programmability and intelligence [1] - Ericsson's executives discussed 5G differentiated services, programmable networks, AI integration, and 6G planning during the "Imagine Live" event in Beijing [1] Group 2 - 5G differentiated services provide revenue growth opportunities for operators, shifting from uniform "best-effort" services to tailored connectivity for various applications and user needs [2] - The enterprise market requires more predictable and reliable connections to support critical business applications, while the consumer market faces challenges due to limited willingness to pay [2] - Ericsson's solutions include performance-based differentiated services like network slicing, AI-driven wireless access solutions, and standardization of APIs to lower development barriers [2] Group 3 - To address low consumer willingness to pay, Ericsson suggests tiered package designs, offering basic, video call, and low-latency gaming packages, as well as bundling high-value scenarios like AR glasses [3] Group 4 - The integration of AI and networks enhances operational efficiency and intent recognition, with over 85% of Ericsson's wireless network functions capable of intent-driven service demand recognition [4] - AI supports low-latency connections for edge and endpoint computing scenarios, facilitating data interaction for devices like mobile AI assistants and AR glasses [4] - Collaborations with companies like Toyota, NVIDIA, and Google aim to advance AI and 5G network integration for applications such as cloud rendering and autonomous driving [4] Group 5 - The development of 6G is focused on incorporating differentiated connectivity capabilities, with AI deeply integrated for self-optimizing intent recognition and dynamic resource allocation [4]