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The First 6G AI Competition Has Been Launched By OPPO

The First 6G AI Competition Has Been Launched By OPPO

OPPO, the world’s leading smart device manufacturers and innovators, officially launched the first 6G AI Competition on December 24, 2021 (Beijing time) on DataFountain (a leading Big Data & AI competition platform).

The deep integration of wireless communication and artificial intelligence (AI) has become an important direction for the construction of future wireless communication systems. At present, many researches with good results on AI solutions for specific modularization problems of 5G wireless communication systems have been carried out in academia and industry. At the same time, with the evolution from 5G to 6G, researchers have once again obtained the opportunity to ponder, define and build a new generation of wireless communication systems. In this process, many constraints in current system can be relaxed, and the direction and depth of the integration for 6G and AI can further be expanded.PREDICTIONS SERIES 2022

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Based on the above background, OPPO launched the “6G AI Competition”, which aims to combine the strengths of all parties and the promotion of the competition to systematically and comprehensively study the impact of AI on the future wireless communication system and the solutions for key issues. In the first stage of the competition design, from the perspective of methodological innovation, they introduce some common problems that AI-based solutions need to face, and will comprehensively promote the technological breakthrough and industrial landing of smart 6G.

The competition is open to all the people around the world, regardless of age or nationality. All colleges and universities, scientific research institutions, enterprises, maker teams, individuals, etc. can log on to the official website to register for the competition.

Competition Task:

Task Name: AI based Channel Modeling and Generating
The task considers utilizing AI based method to realize the big set of wireless channel data generation which is seeded from a small set of real channel data. The similarity and diversity of the generated data are jointly used to perform the evaluation.

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