KKashefTelRADIO INTELLIGENCE
THE TECHNOLOGY

Better information.
Smarter radio decisions.

An end-to-end approach: estimate radio conditions, inform adaptation, then evaluate the effect on the link and the experience it delivers.

ESTIMATE. ADAPT. VALIDATE.02 / 08 SCROLL TO EXPLORE ↓
THE DECISION CHAIN

An estimate is only the beginning.

KashefTel’s proposed pipeline follows the effect of radio intelligence all the way to communication performance.

01

Measure the channel

Use available radio observations such as RSRP, RSRQ, SINR and CSI/CQI, subject to testbed access and interface availability.

02

Estimate useful state

Explore AI-based estimation where direct observations are imperfect. Compare with a defined baseline under the same conditions.

03

Inform adaptation

Evaluate how the estimate influences rank adaptation and beamforming. Track the resulting MCS, BLER and HARQ behavior.

WHY THE FULL PIPELINE MATTERS

Lower estimation error is useful.
Better link behavior is the goal.

Evaluation must include the cost of inference, stale information, changing channels and integration constraints. These tradeoffs define whether an approach is useful in a real system.

FROM SIGNAL TO EXPERIENCE

Measure the consequences.

Estimation quality → adaptation decisions → BLER / HARQ → useful throughput / latency. Each connection needs evidence.

START WITH YOUR NETWORK

What could a clearer
radio picture change for you?

Discuss a pilot ↗
5G IN EVERYDAY MOTION

Better connections.
More possibilities.

Application scenarios for evaluation. Simulation results do not establish performance in these environments.

SMART FACTORY

Reliability keeps production moving.

Evaluate wireless delivery for mobile robots and industrial devices as machinery and obstructions change the radio environment.

Reliability · RetransmissionsExplore a pilot ↗
CONNECTED MOBILITY

Intelligence that moves with you.

Explore changing channels, beam decisions and modeled latency along a vehicle’s route.

Latency · Link continuityExplore a pilot ↗