MediaTek's recently published vision for 6G offers a glimpse into the future of global wireless connectivity. We've played a significant role enabling mass-market 5G with our ground-breaking Dimensity chips, and we have already started defining what 6G will be. Under Simplexity, Optimization and Convergence “SOC” principles, we outline our 6G Vision, its key drivers, technology enablers and timeline to commercialization.
MediaTek envisions 6G will expand the digital transformation of our society, further advancing the performance and adoption of existing use cases, while enabling emerging ones. Such an ambitious goal necessitates an overall system design that can cater to the extreme performance demands of these markets while also being inherently adaptive to their various data consumption models and deployment scenarios in a fully secure and sustainable manner.
While intuitively highly complex, this exercise requires following from the outset, key practical technology principles so our vision can become reality i.e. Simplexity, Optimization and Convergence or “SOC”:
We define Simplexity as the balance between the necessary additional complexity in creating 6G devices and infrastructure, and the overall drive for simplicity. We expect this to enable the necessary performance leap while significantly reducing the processing requirements per bit delivered, in order to keep cost and energy consumption within realistic bounds.
Energy efficiency will represent both a challenge and an opportunity for 6G to make a real difference. Societal sustainability goals will require a reduction in overall network energy footprint whilst delivering orders of magnitude increases in performance. User devices will always exhibit thermal and energy storage challenges, and these will need to be overcome to enable higher practical data rates, while also enabling new device form factors for advanced, immersive applications.
Optimization must be guided by practical user experiences, and we expect it to focus in three new key directions: heterogeneous radio access architecture, artificial intelligence and machine learning, and application-specific cross-layer design.
We envision Artificial Intelligence and Machine learning will allow the simplification of 6G deployment and everyday operation. It will be integral to all aspects of network and device operation, iteratively learning to systematically improve 6G system performance whether in real-time (e.g. link adaptation, scheduling, mutual awareness between applications and radio layers), near-real-time (e.g. load balancing, interference management) or non-real-time (e.g. network planning). This is needed to support goals such as maximizing user experience, optimizing cost efficiency, and minimizing the energy consumed.
Convergence between peer domains is an opportunity to tackle challenges on coverage, affordability and energy efficiency. For example, this means between devices and network nodes, between spectrum regimes, between access, front- and backhaul, between device-to-device and base station to device access, between terrestrial and non-terrestrial access, between communication and computing, etc.
We envision that the 6G architecture should be fully adaptable to offer the best networking topology to serve any given data consumption model between communication endpoints, whether directly between devices in a local mesh, through traditional terrestrial network infrastructure, or relayed via airborne or satellite equipment. To this end, and from a radio architecture standpoint, Hybrid Nodes will play a major role in supporting the networking functionality necessary to cooperatively determine, with or without network involvement, the best corresponding radio networking topology.
Wireless Spectrum will be a fundamental driver for the 6G system design. To cope with the ever increasing demand to provide a growing number of services and use cases, undoubtedly the system will need to grow beyond existing frequency ranges into new spectrum such as the 7-24GHz range and the sub-THz range. In addition, it will need an improved utilization and ease of re-farming existing spectrum assets (for both terrestrial and non-terrestrial deployments). Different deployment scenarios and topologies will be required to allow the different frequency ranges to be used optimally.
