Case Studies
As 5G-Advanced networks evolve and the industry prepares for 6G, Qualcomm Technologies worked with Keysight to explore how digital modeling can help engineers better understand radio frequency performance before deployment.
The collaboration connects high-fidelity simulation, lab-based emulation, and over-the-air validation. Using Channel Studio RaySim and Qualcomm Technologies’ multiple-input multiple-output algorithms, the companies demonstrated a repeatable approach for evaluating next-generation wireless systems under realistic operating conditions.
Massive multiple-input multiple-output (MIMO) is a critical capability for 5G-Advanced and emerging 6G networks. It helps improve capacity, coverage, and spectral efficiency by using large antenna arrays and advanced beamforming techniques. As wireless systems grow more complex, engineers need more precise ways to understand how these capabilities will perform in operating environments.
Radio frequency (RF) behavior is shaped by the physical conditions of each deployment site. Buildings, terrain, mobility, antenna placement, and propagation paths can all influence signal quality. Beamforming and precoding strategies that perform well in simulation may behave differently once deployed in the field.
At the same time, the industry is working to apply artificial intelligence (AI) within the radio access network (RAN). AI-based techniques require high-quality channel data and repeatable benchmarks so engineers can train, validate, and compare algorithms with confidence. Without reliable datasets and consistent test conditions, it becomes harder to predict real-world performance.
Qualcomm Technologies and Keysight addressed this need by connecting virtual modeling with lab validation and field measurements. The objective was to help bridge the gap between algorithm design, controlled testing, and operating network behavior so engineering teams can make better decisions earlier in the development cycle.
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