Student Topics

Higher Order B-Splines for Accurate and Efficient Interpolation

At EMS we conduct extensive radio measurement campaigns, which are the basis for future radio standards. This measurement data boils down to gigabytes per second of raw data collected over hours of measurement campaigns1. Afterwards, we can compute the estimated radio channel parameters from those measurements. A major bottleneck is the interpolation of the measured antenna characteristic2.

Influence of Low Precision Datatypes on Interpolation Algorithms

At EMS we conduct extensive radio measurement campaigns, which are the basis for future radio standards. This measurement data boils down to gigabytes per second of raw data collected over hours of measurement campaigns1. Afterwards, we can compute the estimated radio channel parameters from those measurements. A major bottleneck is the interpolation of the measured antenna characteristic2.

Quantifying the Performance of Multidimensional Channel Sounding and Parameter Estimation

Measuring and characterizing the wireless propagation channel is of utmost importance for developing applications at most recent and unexplored frequency bands. However, since there are no off-the-shelf hardware solutions and no proven algorithms for new frequency bands, doing channel measurements itself is experimental, and the concepts of different research institutions and labs will widely differ. To still develop one common understanding of the wireless propagation channel, concepts for verifying and quantifying the accuracy of the channel sounding results are required1.