Wireless communication systems have progressed through a series of generational upgrades, each providing significant improvements in speed, capacity and features:
- 1G (1980): Marked the start of mobile communication with analog vocal services.
- 2G (early 1990s): Introduce digital transmission, improving vocal quality and allowing text messaging.
- 3G (2000): Provided faster data speeds, supporting mobile internet, video calls and multimedia applications.
- 4G (2010s): Activated high -speed mobile broadband via technologies like LTE, allowing video streaming, online games and voice on IP.
- 5G (from 2019): Offers an ultra-faible latency and a high bandwidth, and supports a wide range of connected devices, including those used in smart cities, autonomous vehicles and the Internet of Objects.
Each generation has played a key role in the training of the modern digital landscape, allowing new technologies and transforming the way people communicate and access information. But what is the next step? 6g, of course.
Shiwen Mao, director of Wireless engineering research and education center at the University of Auburn and professor in the Department of Electrical and IT engineeringtook the time to answer a few questions about the subtleties of 6G.
How will 6G technology be used?
Shiwen Mao: Unlike previous generations which mainly focused on a single wireless technology, such as multiple access to the large-band code division in 3G or LTE in 4G, 6G encompasses a wide range of areas of application and extends far beyond traditional mobile phones. 6G technologies will be integrated into smartphones and portable devices, AR / VR helmets and smart glasses for immersive entertainment. They will also feed smart houses for safety monitoring and energy -efficient appliances, allow autonomous driving in smart vehicles and support automation in factories and supply chains.
The mobile phones we use today will be radically different because of 6G?
Mao: Rear compatibility remains a crucial consideration in the development of wireless systems. For example, more recent Wi-Fi routers remain compatible with older devices. Likewise, in cellular networks, basic stations can return to older generation technologies during periods of low traffic to reduce operational costs. The deployment of 6G will take years and the revision of the network infrastructure each decade presents a significant financial burden for service providers.
However, new devices with new emerging features. Such an example is the human spindle – a portable gadget designed as an alternative to smartphones. It attaches to clothes and uses a laser projector to display the user output. The device incorporates a virtual assistant fueled by a language model to perform tasks such as web search, messaging and real -time translation.
In addition, helmets and smart glasses evolve from simple display appliances in full-fledged spatial platforms. Taking advantage of artificial intelligence (AI), camera sensors and computer vision, these devices map and interact with the physical world, allowing users to control applications with finger gestures or hand movements, eliminating the need for traditional screens or keyboards.
In conclusion, mobile phones are very likely to evolve considerably with 6G, becoming more integrated with portable and spatial technologies. Although they do not disappear entirely in the short term, their role and their form factor should change considerably.
In what role will the continuing evolution of AI play in 6G compared to 5G?
Mao: 6G’s most disruptive technology is probably AI. The convergence of AI and communications will make the first AI-Native networks, where AI models will be executed in mobile devices, network nodes and in the cloud. On the one hand, the traditional wireless system and network design will be revisited and redesigned with AI for considerably improved efficiency and resilience. On the other hand, various compatible applications, for example, search engines, the content generated by AI, the analysis of feelings and chatbots, will be better supported on mobile devices.
When will 6G technology be launched with commercial products, and what could these products be?
Mao: In mid-2025, 6G standardization progressed regularly, with key stages affected and a clear roadmap described by international organizations and industry stakeholders. Organizations such as Third generation partnership project and the Radiocommons radiocomunation section Direct this process, which should continue through the second half of the decade. The first 6G commercial deployments were scheduled for the early 2030s.
Are there potential drawbacks at 6G?
Mao: Generational cohorts – baby boomers, generation X, generation Y and generation Z – are defined by their years of birth and are often associated with distinct characteristics and cultural influences. Likewise, previous generations of wireless systems have been characterized by signature technologies and basic applications. However, this clarity begins to blur with 5G and 6G, where a wide range of heterogeneous wireless technologies and applications is grouped in a single generational label. Consequently, the definition of 6G has become more and more wide and practically any technological progression can be classified as part of it.
Another concern is the substantial cost associated with the upgrading of network infrastructures each decade, which represents an important financial burden for service providers and users (for example, factory owners).
The rapid advancement of wireless systems also has environmental challenges. These include high power consumption of the 5G and 6G basic stations, the growing volume of electronic waste and exhausted batteries, and the accumulation of satellite debris, which presents risks for operational satellites.
While AI improves the design and efficiency of 6G systems, it introduces its own set of challenges. We often lack in -depth understanding of the operation of internal AI models, and there is generally no guarantee concerning the reliability or accuracy of their results. If they are trained on defective or incomplete data, AI systems can produce biases or misleading results.
Thanks to University of Auburn