Spectrum AI expands commercial CBRS network capacity fivefold

Federated Wireless launched Spectrum AI to increase shared CBRS network capacity by addressing radio frequency physics directly.

Operators deploying the platform across hundreds of live commercial Citizens Broadband Radio Service (CBRS) networks report up to a fivefold expansion in network capacity. These hardware-independent performance gains occur without requiring additional spectrum acquisitions, new tower installations, or supplementary physical infrastructure.

The software architecture introduces physical AI to real-world physics, directing computational power at propagation conditions, interference dynamics, and spectrum assignments. These three physical variables determine overall wireless network performance.

Most existing AI tools operating within the telecoms sector automate higher-level workflows functioning strictly above the actual network layer. Federated Wireless built this system to operate exclusively at the radio frequency layer. This base layer represents the exact location where engineers physically design, coordinate, and optimise wireless hardware. The platform accuracy improves with every live deployment it processes.

Spectrum AI operates as an automated spectrum management system engineered to deliver step-function gains across two specific operational levels: spectrum efficiency and spectrum performance. The direct result, measured extensively in live deployments, provides network operators with usable high-quality spectrum. 

Engineering teams operating live commercial networks extract up to 50 percent more usable high-quality spectrum capacity through machine-driven coordination. This AI-driven coordination secures greater efficiency out of existing spectrum allocations. Simulation speeds during the planning phase have increased by a factor of 100–1,000x.

The platform delivers propagation modelling accuracy exceeding 90 percent, holding precision within a sub-0.5 decibel margin. Radio frequency engineers can use these metrics to plan networks relying on exact coverage and interference predictions. Interference coordination accuracy improves by up to 20 decibels within active, live shared-spectrum environments.

Operators targeting equivalent coverage and capacity metrics report up to a 50 percent reduction in required site counts. Lowering the total number of physical cell sites reduces total deployment costs by up to 40 percent on every new infrastructure build. Improving the underlying economics on every build changes the commercial viability of extensive CBRS and shared spectrum deployments.

Iyad Tarazi, CEO of Federated Wireless, said: “Most AI in the wireless industry operates above the physical layer, automating workflows, managing operations or optimising software. Spectrum AI works at the radio and propagation level—the physical foundation where coverage, interference, and capacity are actually determined.

“Wireless networks contain far more latent capacity than operators have been able to access. The spectrum was always there, but the computational tools to find it and use it at scale were not. Spectrum AI changes that. Operators can now treat spectrum coordination as a continuous optimisation problem rather than a one-time engineering exercise, and every network the platform touches gets smarter, more efficient, and more profitable over time.”

Real-world telemetry versus simulation models

Most AI systems designed for wireless network management rely primarily on simulated environments for training data. Federated Wireless abandoned this simulation-only approach, grounding its data architecture in production telemetry sourced from hundreds of live commercial networks.

The platform runs on five foundational capabilities. It utilises live spectrum coordination data generated continuously across the largest commercial shared-spectrum footprint in the US, cross-referencing nationwide geospatial intelligence accumulated from more than a decade of real-world spectrum assignments, interference events, and propagation observations. This historical dataset provides a training foundation characterised by commercial relevance that simulation models cannot replicate.

Business intelligence and Coverage IQ data supplement this baseline by supplying address-level coverage, service qualification, and market intelligence. This insight connects radio frequency performance directly to subscriber acquisition and revenue outcomes, keeping all analytics grounded in first-principles RF modelling.

Deepak Das, VP of Solutions and Product at Federated Wireless, explained: “The accuracy Spectrum AI delivers comes from AI-native propagation models grounded in RF physics and continuously improved using measurements from real-world wireless environments.

“Every deployment contributes propagation data, interference observations, and deployment outcomes back into the platform, creating a compounding intelligence advantage that benefits every operator on the system. For operators, that translates directly into more capacity from the spectrum they already hold, fewer sites to build, and better economics on every deployment.”

Integrating the ‘Adaptive Network Planner’ for lifecycle management

The platform pairs with the Adaptive Network Planner (ANP) to manage both halves of an operator’s network lifecycle. Spectrum AI handles active hardware by improving networks already transmitting data on the air.

Engineering teams rely on the ANP to plan new networks before committing capital expenditure. The ANP applies the same underlying physical intelligence to network planning, qualifying coverage, capacity, and economics with physics-accurate precision.

The initial software release delivers spectrum deconfliction and performance improvement specifically for CBRS and 6 GHz spectrum bands. The launch version also includes enhanced antenna support capabilities.

Federated Wireless designed the system for large and mid-sized operators deploying hardware in shared spectrum environments. This primary operator group includes Priority Access License users maintaining protected allocations and General Authorized Access users operating within dynamic CBRS networks.

Enterprises managing networks constrained by incumbent-protection mandates or heavy coordination requirements can use the system to navigate physical interference while maximising data throughput.

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