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Characterization of Spatial-Temporal Channel Statistics from Measurement Data at D Band

Chathuri Weragama, Joonas Kokkoniemi, Mar Francis De Guzman, Katsuyuki Haneda, Pekka Kÿosti, Markku Juntti

TL;DR

This work addresses D-band mmWave propagation for 6G by building a measurement-based GBSM that captures spatial-temporal statistics in LOS/NLOS outdoor and indoor settings. It derives a channel impulse response using a sum-over-paths formulation $\mathbf{H}=\sum_{l=1}^{L}\delta^F_l(f,\tau_l)\delta^A_l\mathbf{a}_r(\phi_l)\mathbf{a}_t^H(\theta_l)e^{-i(2\pi f\tau_l+\beta)}$, and identifies appropriate distributions for path gain, excess delay, and the number of paths, including a log-normal angular spread input for the array responses. The study validates the model using MED, showing reasonable agreement with empirical data, while highlighting limitations from finite measurement samples and the challenge of joint-distribution estimation. The results enable realistic synthetic channel generation for D-band MIMO simulations and signal-processing algorithm development, with practical impact for 6G design and research. Future work calls for larger measurement campaigns and data augmentation (e.g., ray-tracing calibration) to improve joint-statistics analyses across environments.

Abstract

Millimeter-Wave (mmWave) (30-300 GHz) and D band (110-170 GHz) frequencies are poised to play a pivotal role in the advancement of sixth-generation (6G) systems and beyond with increased demand for greater bandwidth and capacity. This paper focuses on deriving a generalized channel impulse response for mmWave communications, considering both outdoor and indoor locations for line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. The analysis is based on statistical insights obtained from measurements conducted at distinct locations with a center frequency of 142 GHz, examining parameters such as path gain, delay, number of paths (NoP), and angle distributions. Whereas different distributions serve as candidate models for the gain of LOS communications, only specific distributions accurately describe the NLOS gain, LOS and NLOS delay, LOS and NLOS NoP, and LOS and NLOS angular distributions. The channel is modeled based on geometry-based stochastic channel modeling (GBSM) with parameters derived from the statistical analysis. The maximum excess delay is used as a metric to evaluate the performance of the proposed model against empirical data.

Characterization of Spatial-Temporal Channel Statistics from Measurement Data at D Band

TL;DR

This work addresses D-band mmWave propagation for 6G by building a measurement-based GBSM that captures spatial-temporal statistics in LOS/NLOS outdoor and indoor settings. It derives a channel impulse response using a sum-over-paths formulation , and identifies appropriate distributions for path gain, excess delay, and the number of paths, including a log-normal angular spread input for the array responses. The study validates the model using MED, showing reasonable agreement with empirical data, while highlighting limitations from finite measurement samples and the challenge of joint-distribution estimation. The results enable realistic synthetic channel generation for D-band MIMO simulations and signal-processing algorithm development, with practical impact for 6G design and research. Future work calls for larger measurement campaigns and data augmentation (e.g., ray-tracing calibration) to improve joint-statistics analyses across environments.

Abstract

Millimeter-Wave (mmWave) (30-300 GHz) and D band (110-170 GHz) frequencies are poised to play a pivotal role in the advancement of sixth-generation (6G) systems and beyond with increased demand for greater bandwidth and capacity. This paper focuses on deriving a generalized channel impulse response for mmWave communications, considering both outdoor and indoor locations for line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. The analysis is based on statistical insights obtained from measurements conducted at distinct locations with a center frequency of 142 GHz, examining parameters such as path gain, delay, number of paths (NoP), and angle distributions. Whereas different distributions serve as candidate models for the gain of LOS communications, only specific distributions accurately describe the NLOS gain, LOS and NLOS delay, LOS and NLOS NoP, and LOS and NLOS angular distributions. The channel is modeled based on geometry-based stochastic channel modeling (GBSM) with parameters derived from the statistical analysis. The maximum excess delay is used as a metric to evaluate the performance of the proposed model against empirical data.

Paper Structure

This paper contains 23 sections, 5 equations, 19 figures, 10 tables.

Table of Contents

  1. Introduction
  2. Geometric Stochastic Channel Model
  3. Channel Model
  4. Parameters of the Model
  5. Channel Measurement Data
  6. Modelling Methodology
  7. Data Manipulation
  8. Analysis of Distributions
  9. Maximum Excess Delay
  10. Statistical Channel Parameters
  11. Power Delay Profile
  12. Normalized Power Distribution (NPD)
  13. Normalized Delay Distribution
  14. The Number of Paths
  15. Angular Spread
  16. ...and 8 more sections

Figures (19)

  • Figure 1: Normalized power delay profile of indoor locations.
  • Figure 2: Normalized power delay profile of outdoor locations.
  • Figure 3: Normalized power distribution for line-of-sight scenario in indoor locations.
  • Figure 4: Normalized power distribution for line-of-sight scenario in outdoor locations.
  • Figure 5: Normalized power distribution for non-line-of-sight scenario in indoor locations.
  • ...and 14 more figures