According to People’s Daily Online, recently, Chinese scientists have successfully developed an ultra-broadband optoelectronic integrated system, which has achieved high-speed wireless communication with full-frequency-band coverage and flexible tunability for the first time. This breakthrough is expected to ensure smoother and more reliable 6G wireless communication in the future. The system can realize high-speed transmission of wireless signals at any frequency point within the range of 0.5 GHz (gigahertz) to 115 GHz—this full-frequency-band compatibility and capability is internationally leading. In addition, the system features flexible tunability: when signals are interfered with, it can dynamically switch to a secure frequency band to establish a new communication channel, thereby enhancing communication reliability and spectrum utilization efficiency. The advent of this achievement marks a solid step forward for China in the R&D of 6G core technologies and creates favorable conditions for the in-depth integration of 6G and artificial intelligence (AI).
6G Era Cannot Proceed Without AI Support
If 5G represents the initial stage of “terminal-edge-cloud” collaboration, then 6G aims to achieve in-depth “communication-perception-computing” integration. Professor Wang Xingjun, Vice Dean of the School of Electronics at Peking University, stated that by implanting AI algorithms, this new system will foster more flexible and intelligent AI-enabled wireless networks. These networks can not only be applied in diverse complex scenarios to simultaneously realize real-time data transmission and accurate environmental perception but also automatically avoid interference signals, making network signal transmission safer and smoother.
Among the six major usage scenarios of IMT-2030 defined by the International Telecommunication Union Radiocommunication Sector (ITU-R), “AI and Communication” serves as a service scenario beyond traditional communication. It supports distributed computing and AI applications, including data acquisition, local/distributed computing offloading, distributed AI model training and inference, etc. Typical cases include IMT-2030-aided autonomous driving, autonomous collaboration among medical auxiliary devices, offloading of computation-intensive operations across devices/networks, and the creation of digital twins for prediction purposes. To support these new usage scenarios, IMT-2030 needs to add new AI capabilities and perception capabilities in addition to its traditional communication capabilities.
The industry generally recognizes that collaborative robots will be an important application scenario for future 6G, but such robots rely on AI services with low latency and high accuracy in learning/inference to function. For example, when a person uses voice to instruct a robot to retrieve an object, the robot must first understand the natural language instructions and then plan the sub-tasks for each robot. Both understanding and planning rely on large, efficiently trained (language) models, which consume significant computational and memory resources. Using local vision or control models, the robot can detect objects from perceived images and plan the path trajectories for sub-tasks and make corresponding control decisions.
In this way, AI robots can collaborate with networks, leveraging the superior AI capabilities provided by the network to plan complex tasks. Robots can also cooperate with each other across the network, improving the performance of their local models through collaborative training, sharing, and learning from each other’s experiences.
The Convergence of 6G and AI is Driving a Revolution in Terminal Form and Interaction Methods
In the wave of rapid evolution of digital technology, the in-depth integration of 6G and artificial intelligence (AI) is breaking through the boundaries of traditional communication, driving the transformation of terminal form from a single tool to a multi-intelligent carrier, and the interaction mode is also moving from “humans adapting to machines” to a new stage of “machines understanding humans”, injecting strong momentum into the future human-machine-thing collaborative ecosystem.
In the past, mobile phones were almost the sole core terminal for personal communication and intelligent interaction, with functions limited to information transmission and basic applications. However, the combination of 6G and AI has completely broken this pattern, spurring diversified innovations in terminal form factors. On one hand, wearable devices such as smart glasses and flexible bracelets become “external extensions of the human body,” achieving hands-free real-time interaction through the fusion of lightweight AI models and multiple sensors. For instance, based on 6G’s low-latency network, smart glasses can recognize the surrounding environment in real time and provide personalized services such as navigation and translation. On the other hand, terminals are no longer isolated entities but form a “cluster of intelligent agents” with multi-terminal collaboration. Mobile phones, smart home devices, and vehicle-mounted terminals leverage 6G’s integrated communication-perception-computing capabilities to achieve data sharing and task division. For example, when users are commuting, in-vehicle terminals can seamlessly take over unfinished meeting appointments on mobile phones, while simultaneously linking with smart homes to adjust the indoor temperature in advance.
The transformation of interaction methods is more intuitive. In the past, users had to complete tasks through touch-based APP operations; today, however, 6G and AI have made “intent-based interaction” possible. Leveraging the high speed of 6G and AI’s natural language processing and computer vision technologies, users can express their needs simply through voice, gestures, or even eye contact, and the smart terminal can quickly decipher the intent and call upon resources to execute it. For example, if a user says, “Organize today’s work documents and share them with the team,” the terminal will automatically retrieve relevant files, classify and organize them, and then transmit them in real time via the 6G network—no need to manually open multiple applications. Meanwhile, content services are also shifting from “retrieval-based” to “generation-based”. AI can generate text, video and other content on demand based on user preferences and combined with scene data acquired in real time by 6G. For example, when traveling, the terminal can generate personalized travel guides containing local attractions and food in real time.
6G’s Intelligent Journey Faces Numerous Challenges: Urgent Need to Strengthen “Software-Hardware” Infrastructure Development
Despite its bright prospects, 6G’s journey toward intelligence faces numerous challenges.
First is the “data hunger” issue: training network AI models requires massive amounts of high-quality data, but this data is scattered among operators, terminal manufacturers, and internet companies, making it difficult to share and utilize. For example, OpenAI needed to integrate a large volume of text data from around the world—including web content, books, and papers—to train its GPT series models. Under 6G networks, this involves coordination and cooperation of multi-party data, which currently faces significant obstacles.
Second is the need to balance “real-time performance” and “complexity”: communication decisions need to be completed within milliseconds, while complex AI algorithms are computationally intensive. Making optimal decisions in a short time tests both the algorithm and computing power. Taking autonomous driving scenarios in intelligent transportation as an example, vehicles need to make decisions based on road conditions and the driving status of other vehicles in an extremely short time. Achieving real-time response for complex AI algorithms under 6G networks is extremely difficult. Furthermore, the consequences of a breach of the core intelligent network system are severe, thus requiring even stronger security measures.
Therefore, strengthening the development of both “software and hardware” infrastructure is the top priority. In terms of data, it is necessary to establish relevant mechanisms to promote cooperation among data owners such as operators, terminal manufacturers, and internet companies, and facilitate the sharing and utilization of data. For instance, building secure data trading platforms to enable data circulation while ensuring data security and privacy.
In terms of computing power, it is essential to vigorously advance advanced computing technologies such as quantum computing and edge computing to improve computing efficiency and meet the computing needs of complex AI algorithms. For example, deploying powerful computing servers at the network edge can reduce data transmission latency and enable rapid processing of local data.
In terms of security, more advanced encryption algorithms and network security protection technologies should be developed to build a multi-layered security protection system to ensure the security of core intelligent systems. For example, blockchain technology can be used to encrypt and verify data storage and transmission, preventing data tampering and theft.
Only by strengthening the development of “software and hardware” infrastructure can the integration of 6G and AI better reshape the communication ecosystem, propel communication technology to new heights, and provide solid support for the intelligent development of various industries.
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Source: Communications Information News