Point-Data for Site-Specific Mid-Band Radio Propagation Channel Statistics in the Indoor Hotspot (InH) Environment for 3Gpp and Next Generation Alliance (NGA) Channel Modeling

Extensive work has been carried out in the past year by various organizations in an effort to determine standardized statistical channel impulse response (CIR) parameters for the newly-released FR3 mid-band spectrum ($7.25 \text{GHz}-24.25 \text{GHz}$) [1]–[5]. In this work, we show that the wireless community currently lacks a unified method for presenting key parameters required for transparency and utilization by several constituencies when presenting propagation data for use by standard bodies or third parties to create statistical CIR models. This paper aims to solve the existing problem by offering a standard method to provide key propagation parameters in a point-data format that supports both statistical and site-specific channel characterization. The proposed method offers tremendous promise when data contributors use the minimum agreed-upon measurement and processing specifications such as bandwidth, antenna beamwidth, and noise threshold level. As shown here, the point-data format enables multiple contributors to create channel model standards or pool measurement data to create larger datasets for exploring ray-tracing (e.g. site-specific) channel modeling or training in AI/ML propagation work, and to ensure the most accurate model using a larger dataset that is continually expanded through measurement contributions. The point-data approach includes sitespecific point-by-point propagation data while readily supporting the creation of commonly-used cumulative distribution function (CDF) plot. The indoor hotspot (InH) datasets collected in Spring 2024 at 6.75 GHz and 16.95 GHZ by NYU WIRELESS [1]–[3] are provided for the first time in point-data form, to augment statistical models previously presented solely as CDFs, in order to demonstrate how a standardized approach to measurement data could allow others to utilize the site-specific locations and key channel parameters observed at each location, to better understand, vet, and build upon statistical or site-specific CIRs from the contributions of many different data sources.