Data driven ways to share wireless frequencies for better 6G networks
Data-Driven Spectrum Access Technologies for 6G
Information Theory
Summary
As mobile data use grows quickly, especially with 5G and future 6G, finding room on the airwaves is a big challenge because most frequencies are already in use. The paper explains new techniques that use artificial intelligence and advanced antenna technology to let 6G systems share spectrum without interfering with current users like satellites and radar. These methods help protect existing services while still allowing fast and efficient cellular communication. This means 6G can work smoothly even where spectrum is crowded.
What this means in practice
- •For cellular network engineers: Implement AI-driven spectrum sharing techniques to maintain performance while coexisting with satellite and radar systems below 15 GHz.
- •For satellite network operators: Use base station detection methods to enable real-time spectrum access without causing harmful interference to satellite receivers.
Authors
Foad Sohrabi, Harish Viswanathan, Sivarama Venkatesan, Jinfeng Du, Aliye Özge Kaya, Navin Hathiramani, Pavan Koteshwar Srinath
Abstract
The surge in global mobile traffic, driven by 5G adoption and emerging applications, necessitates new spectrum allocations for 6G systems. With most major swaths of spectrum below 15 GHz already allocated to other services, co-existence between cellular and incumbent services such as satellite or radar systems is critical to make such spectrum accessible for 6G. At the same time, the advent of artificial intelligence offers a new opportunity for designing more efficient spectrum sharing techniques. This paper presents four novel data-driven spectrum access techniques to enable efficient use of spectrum for the 6G era: 1) co-existence technique for efficient protection of fixed incumbent receivers within an established protection area; 2) data-driven approach for protecting satellite receivers via control of radiated power above the horizon; 3) spectrum sensing-based fast-time-scale physical resource block blanking; and 4) base station-based spectrum occupancy detection to enable fast-time-scale spectrum sharing with satellite and non-terrestrial network incumbents. These techniques leverage artificial intelligence and extreme multiple-input multiple-output capabilities to enable efficient spectrum co-existence/sharing while maintaining cellular network performance.