Conventional spectrum management is generally a static process in which users are assigned exclusive rights to bands of frequencies to be used in specific geographical regions. In this model, the main strategy for sharing spectrum is to partition the available spectrum into finer and finer spectral swaths. This forces industry to develop more efficient modulation schemes, where more bits of data can be transported per unit of frequency (hertz). Although many modulation techniques have been developed over the past 20 years, we are rapidly approaching the number of bits per hertz that can be transported efficiently.
Once allocations are set, spectrum management is composed of verification and enforcement of allocations in a rather manual fashion. One example of this could be a government agency employing a manual, human-intensive RF interference hunting approach using only the most basic tools such as spectrum analyzers and large form-factor directional finding tools. Their goal would be to identify and locate violators of spectrum access agreements, and then apply appropriate regulatory methods to protect their spectrum from interference.
The key problem with this approach is posed by today’s spectrum crunch. With growing numbers of competing users interfering with each other in a 5G, Internet of Things world, static approaches to spectrum management simply aren’t practical. The President’s recent directive to federal agencies to study ways to open up broad swaths of the wireless spectrum for public use, in response to pleas from cellphone carriers and other companies, is a good start to easing the spectrum crunch, but it will clearly take many months (or years) before studies are completed and solutions are deployed.
A better, more sustainable solution for spectrum management should feature highly concurrent, dynamic, seamless, and at least semi-autonomous (if not fully self-governing) allocation of the spectrum for multiple competing users with different data capacity and data traffic requirements. The cognitive sensing of actual spectrum usage in real time will prove a key enabler of autonomous network awareness and bandwidth management.
Proactive and dynamic spectrum awareness and management approaches such as this will require three components:
By applying these new methods for spectrum monitoring, dynamic spectrum access, and resource allocation, a scaled solution for spectrum management can avoid excessive “human-in-the-loop” requirements while allowing for enforcement of spectrum access agreements.
Based on LGS CEO Kevin Kelly interview with ‘Microwaves & RF’ magazine, Jan. 2017.