A Dynamic Spectrum Footprint Adaptation Framework for Collaborative Spectrum Sharing

摘要

Spectrum sharing is a reality closer than one might think. Dynamic and intelligent spectrum allocation, where different networks collaborate to optimize spectrum usage jointly, is required to overcome spectrum scarcity. Artificial Intelligence (AI) can play a major role to solve this complex problem in dynamic environments with continuously changing data requirements. A part of the problem can be solved by using smart AI-enabled flow control. Smart flow control can have a major impact on the spectrum footprint of mobile networks where it can optimize the Quality of Service for the own and neighboring networks. This paper presents the architecture and the basic principles of the dynamic spectrum footprint control based on flow prioritization of the SCATTER radio system, a wireless endto-end communication system that participated in the DARPA Spectrum Collaboration Challenge. The flow control mechanism is a policy-based framework.