Article by Dr. Andrew L. Drozd
Published by The Fast Mode on January 20, 2021
Carriers and providers continue to focus on network utilization and optimization to better monetize services, but remain limited in their ability to optimize spectrum utilization for the same purpose. Creatively monetizing network and spectrum utilization continues to be a vexing industry challenge.
A significant barrier is the regulatory limits on spectrum utilization and access. Carriers, mobile network operators, and even spectrum access system providers are bound by limited spectrum resources that are governed by static frequency policies at the federal level, yet the demand for spectrum access and the ubiquity in wireless devices continues to grow exponentially.
Ripping the covers off for a moment, an impediment to a true, successful 5G rollout is the industry “vertical” model of the centralized cloud service, internet provider, and enodeB large carrier cell towers. Why not instead deploy a distributed small cell with peer-to-peer or multi-access mobile edge computing (MEC) architecture, that adjudicates spectrum in real time via an intelligent spectrum brokering approach that offers true democratization of spectrum?
Moreover, by integrating a new spectrum approach within existing architectures, we can move from a static (stop-and-go or discrete) micro slice architecture with inherent latencies to dynamic (continuous) micro slicing, where data flow is based on the whims of dynamic spectrum performance.
In this AI-driven, dynamic frequency model, the frequencies and related mesh network applications are continually updated in real time. As well, devices must be semi-autonomous in their ability to operate without human intervention to the extent necessary (with humans on, not necessarily in the loop). Can we build smart algorithms that are service-level agreement (SLA) driven? How can we best leverage AI and machine learning (ML) to enable wireless devices to be “self aware,” self-adjust, and negotiate the ever-changing policy limits and environmental conditions they encounter? Can devices be trained not to hog up spectrum when they shouldn’t and release it to others as necessary and to develop monetized “rewards” for such actions?
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