name: PDF
full_form: Policy Decision Function
context: The reference CDF curve was determined with a very fine constant step size measurement grid using a 1o step size in ï± and ï¦. The need for scaling the PDFs by sin(ï±) is highlighted in Figure G.3.3.1-1 for an EIRP spherical coverage CDF analysis based on 10000 random UE orientations with a 1o constant step size grid. While the CDF curves in Figure G.3.3.1-1a are based on the PDF scaled by sin(ï±), the curves in Figure G.3.3.1-1b were not using the ï± dependent scaling. Clearly, the sin(ï±) scaling makes the CDF curves converge to the reference CDF curve for this very fine measurement grid, while the simulated CDFs without the sin(ï±) scaling of the PDF are spread rather wide and can therefore not be used for CDF analyses. (a) (b) Figure G.3.3.1-1: Sample CDF Analyses for a very fine 1o constant step size measurement grid. a) with the sin(ï±) scaling of the PDF and b) without the ï± dependent scaling. At the 50%-tile CDF, i.e., the target CDF for Power Class 3, statistical analyses of all 10000
description: Probability Density Function (PDF) is a mathematical function that describes the probability distribution of a continuous random variable. In the context of 3GPP TS 38.810, PDF refers to the probability density function used in the analysis of EIRP spherical coverage and CDF curves.
explanation: While related to telecommunications analysis (EIRP spherical coverage, CDF curves), the core concept of PDF is a mathematical tool, not a specific telecommunications technology or service.
section_title: G.3.3.1EIRP spherical coverage
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