Welcome to our catalyst " Creating a sustainable digital future: low-carbon networks"! --------------------------------------------------------------------- 1.Background The most urgent global challenge we currently face is undoubtedly climate change, which will have far-reaching effects on future generations. To ensure a successful digital and low-carbon transition within the necessary timeframe, it is imperative that we utilize technologies that facilitate rapid emission reductions. Recognizing the significance of its role in combating climate change, China Mobile has released its 2022 Sustainable Development Report, outlining its commitment to implementing green and low-carbon operations to conserve energy and protect the environment. By 2025, China Mobile aims to achieve a minimum 20% improvement in energy efficiency, save over 40 billion kWh of electricity, and contribute to emissions reductions both within the company and society as a whole. Additionally, the GSMA has set an industry-wide challenge to attain a significant breakthrough in achieving zero emissions by 2030, with a target of sourcing at least 70% of all network electricity from decarbonized or renewable sources. However, ambition is just the start. Equally important is the implementation of effective strategies to achieve these goals. In this regard, China Mobile is committed to creating a more sustainable digital future by establishing a low-carbon network. This entails developing and adopting innovative approaches and technologies that minimize carbon footprint while ensuring connectivity and efficiency. The Radio Access Network (RAN), which includes base stations and all associated passive infrastructure like air conditioners, inverters, and rectifiers, is observed to be responsible for 65% of the energy consumption in China Mobile's network. Over 30% of this 65% energy use can be attributable to the cooling systems. Additionally, less than 1% of the mobile network's overall energy is accounted for by renewable sources. Therefore, we have established three primary goals for this Moonshot Catalyst. Goal 1: The enhanced energy-saving features of the base stations aim to achieve “Zero bit Zero watt” within the low-load period, resulting in an extra 15% reduction in energy consumption. Goal 2: To decrease the inefficiency in energy consumption of the base station equipment rooms, with a specific focus on the cooling systems, the Power Usage Effectiveness (PUE) of the equipment rooms will be lowered to 1.3. Goal 3: We will improve the efficiency of electricity conversion from renewable energy sources like solar photovoltaic and wind power to achieve a higher return on investment (ROI). Furthermore, AI-based real-time monitoring and energy management systems will be implemented to ensure a stable power supply to the base stations. Our goal is to increase the proportion of renewable energy in base stations to 15%. By working with industry partners together, China Mobile can pave the way for a greener, more sustainable future and safeguard the well-being of generations to come. 2.Catalyst Innovation solution We leverage end-to-end innovative technologies to develop a greener, low-carbon, and environmentally friendly network through enhancing BS functions, implementing a systemic integration solution for equipment room, and employing intent-driven energy efficiency management. UC1: Energy saving functions enhancement for base stations Enhancing the atomization capabilities of energy-saving technology is crucial for improving existing energy-saving technologies for base stations. Our project has developed an advanced symbol shutdown method. This method utilizes machine learning for traffic pattern identification and achieves intra-timeslot symbol scheduling and coordination. By effectively distinguishing between broadcast/reference signals and data transmission, channel shutdown can be applied within milliseconds. And BBU/RRU/AAU module design ensures that all modules can be shut down independently, and resources are scheduled by pooling based on subscriber-focused and service-focused. This approach guarantees efficient resource allocation and power management. UC2: BS-native AI balancing user experience and energy saving Our project applies native-AI (proposed by 6G) to the existing base stations, fully leveraging the computational capacity to enable machine learning and perception capabilities towards BS, providing more energy-efficient, reliable, and personalized network services. By deeply learning the service patterns and user preferences, BS intelligently optimizes network resource allocation based on real-time requirements. BS analyses measurement reports which are reported in milliseconds, achieving user location and network coverage perception. This enables intelligent network management, making real-time adjustments. Independent of cloud AI platforms, Native-AI enables BS to make real-time decisions, reducing latency and balancing the energy-saving and user performance. UC3: Systemic integration solution for equipment room Using existing sensors such as temperature and humidity sensors within the equipment room, along with meteorological data, and employing time-domain forecasting algorithms like Long Short-Term Memory (LSTM), the temperature can be predicted. Considering the requirements for equipment operation, remote adjustments of air conditioning temperature, fan speed, and other strategies can be implemented through NB-IoT technology. Additionally, based on the actual needs, functions like time-scheduled switch on/off and energy-saving modes can be enabled, effectively managing and optimizing the energy consumption of the air conditioning system, and lowering the Power Usage Effectiveness (PUE) of equipment room. UC4: Stable renewable power introduction. China Mobile wants to increase the power supply proportion of renewable energy to 15%, but solar and wind energy are unstable. We introduced MPPT (Maximum Power Point Tracking) controller into the project, which optimizes the power output of solar panels by continuously tracking and adjusting the operating point to the maximum power point of the panel. Meanwhile the status can be monitored on phone applications. UC5: Intent is introduced into AI platform Intent-driven strategies and visualization are essential components of our project. Our project introduced an intention engine which can identify and translate natural language inputs to obtain energy-saving strategies. Furthermore, we automate the execution of these strategies and provide visual representations of the results, tailored to the specific needs of operation and maintenance. It enables a more seamless and efficient energy-saving strategies by incorporating user intentions and preferences into the decision-making and execution stages, resulting in the L4 level of the Self Intelligent Network. 3.Catalyst Innovation outcome achievement The "Creating a sustainable digital future: low-carbon networks" initiative holds the promise of revolutionizing and addressing Moonshot energy challenges in a number of ways. * Energy Efficiency : The catalyst solution has been verified by deploying it on China Mobile and AIS. It is estimated that additional 1,100 kWh per 5G site will be saved annually with the application of the mentioned energy-saving technologies. China Mobile's whole network with 2G/3G/4G/5G and NB-IoT is expected to save 12% energy by 2023, with the 5G network especially saving 35%. This equates to an annual decrease of 2.9 million tons of carbon emissions.By significantly reducing energy consumption in base stations, it can help to contribute to a substantial decrease in energy usage and carbon emissions and promote sustainable development in the telecommunications industry. * Cost reduction: Network operators could experience significant cost savings as a result of the project's energy-saving strategies and cognitive capabilities. Operators can reduce operational costs and increase profitability by maximizing radio resource use, reducing waste, and incorporating renewable energy sources. * Improved User Experience: The project seeks to strike a balance between user experience and energy efficiency. Network resources will be distributed optimally based on real-time needs with deep learning of service patterns by integrating Native-AI into base stations. Additionally, by analysing measurement reporters at the millisecond level, user location and network coverage will be determined. The user experience can be improved by comprehending their needs. * Scalability and Replicability: The project incorporates open APIs based on TMF autonomous-networks-technical-architecture and supports various vendor configurations, allowing for seamless replication when the operators owns the similar spectrum band resources like AIS Thailand. The adoption of energy-saving technology deployment all around the world is accelerated by its scalability and compatibility by multiple network operators. * Technological Innovation: The project's innovative technologies and strategies have brought new opportunities and prospects to the telecommunications industry. It gives network operators more effective, adaptable, and intelligent solutions, spurring technical advancement and growth in the sector. These features include intelligent capabilities, self-adaptive regulation, and intent-based control. * Contribution to Global Low-Carbon Goals and Sustainable Development: The project supports global initiatives to reduce carbon emissions and combat climate change. It can assist in achieving the global sustainable development goals and ease the transition to a sustainable and environmentally friendly future by offering a reference implementation for base station energy-saving technologies, cutting back on reliance on conventional energy sources, increasing the usage of renewable energy, and lowering carbon emissions. Additionally, partnerships with verticals allow for the development of greener and more widely available 5G solutions, such as in the fields of environmental and animal protection, where 5G has already made a significant contribution to cost savings and carbon footprint reduction by displacing in-person routine inspections and interventions. Even in adverse weather, the sustainability of such methods is further enhanced by the deployment of low carbon 5G network.