[Paper Review] 3-D Statistical Indoor Channel Model for Millimeter-Wave and Sub-Terahertz Bands

Shihao Ju, Yunchou Xing+2 more|arXiv (Cornell University)|Sep 27, 2020

Millimeter-Wave Propagation and Modeling16 references4 citations

TL;DR

This paper proposes a 3-D statistical indoor channel model for mmWave and sub-THz bands (28 GHz and 140 GHz) based on extensive empirical measurements in an office environment. The model uses measured power delay profiles and angular statistics to generate realistic channel impulse responses, with simulation results showing strong agreement between simulated and measured RMS delay spread and angular spread across LOS and NLOS scenarios.

ABSTRACT

Millimeter-wave (mmWave) and Terahertz (THz) will be used in the sixth-generation (6G) wireless systems, especially for indoor scenarios. This paper presents an indoor three-dimensional (3-D) statistical channel model for mmWave and sub-THz frequencies, which is developed from extensive channel propagation measurements conducted in an office building at 28 GHz and 140 GHz in 2014 and 2019. Over 15,000 power delay profiles (PDPs) were recorded to study channel statistics such as the number of time clusters, cluster delays, and cluster powers. All the parameters required in the channel generation procedure are derived from empirical measurement data for 28 GHz and 140 GHz line-of-sight (LOS) and non-line-of-sight (NLOS) scenarios. The channel model is validated by showing that the simulated root mean square (RMS) delay spread and RMS angular spread yield good agreements with measured values. An indoor channel simulation software is built upon the popular NYUSIM outdoor channel simulator, which can generate realistic channel impulse response, PDP, and power angular spectrum.

Motivation & Objective

• To develop a comprehensive 3-D statistical channel model for mmWave and sub-THz bands in indoor office environments to support 6G system design.
• To address the lack of empirical, wideband channel measurements at 140 GHz and above for realistic modeling of future wireless systems.
• To enable accurate simulation of temporal and spatial channel characteristics such as delay spread and angular spread using measured data.
• To provide a standardized, measurement-based reference model for future 6G and THz communication system development.
• To validate the model through comparison of simulated and measured secondary statistics like RMS delay spread and global angular spread.

Proposed method

• Conducted wideband channel sounding campaigns at 28 GHz (2014) and 140 GHz (2019) in a 65.5 m × 35 m office building with 15,000+ power delay profiles (PDPs).
• Used a sliding correlation-based channel sounder with directional horn antennas (15 dBi, 30° HPBW at 28 GHz; 27 dBi, 8° HPBW at 140 GHz) to capture spatially resolved PDPs.
• Derived large-scale path loss and small-scale statistical parameters (e.g., number of clusters, cluster delays, powers, angular spreads) from empirical data for LOS and NLOS conditions.
• Formulated a cluster-based statistical model where each cluster's delay, power, and angular parameters are modeled using log-normal and normal distributions.
• Implemented the model in an enhanced version of the NYUSIM simulator to generate omnidirectional PDPs and power angular spectra (PAS) for validation.
• Validated the model using secondary statistics—omnidirectional RMS delay spread and global RMS angular spread—by comparing simulated and measured cumulative distribution functions.

Experimental results

Research questions

• RQ1 How do the temporal and spatial channel characteristics (e.g., delay spread, angular spread) vary across 28 GHz and 140 GHz in indoor LOS and NLOS scenarios?
• RQ2 Can a statistical 3-D channel model based on empirical measurements accurately reproduce key channel statistics such as RMS delay spread and angular spread?
• RQ3 What are the statistical distributions of cluster delays, powers, and angular parameters (AOD/AOA) in mmWave and sub-THz bands for indoor office environments?
• RQ4 How well does the simulated channel performance match measured data in terms of RMS delay spread and global angular spread across different frequency bands and propagation conditions?
• RQ5 To what extent can a measurement-based statistical model serve as a reliable foundation for future directional and MIMO channel modeling at mmWave and sub-THz frequencies?

Key findings

• The simulated omnidirectional RMS delay spread closely matched measured values: 13.9 ns (simulated) vs. 17.9 ns (measured) at 28 GHz LOS, and 12.5 ns (sim) vs. 13.5 ns (meas) at 28 GHz NLOS.
• At 140 GHz, the simulated RMS delay spread was 3.2 ns (sim) and 3.1 ns (meas) for LOS, and 5.9 ns (sim) and 5.7 ns (meas) for NLOS, showing strong agreement.
• The simulated global RMS angular spread for AOA was within 5° of measured values for 28 GHz LOS, 28 GHz NLOS, and 140 GHz NLOS scenarios.
• For 140 GHz LOS, the empirical distribution was skewed due to limited measurement count, but the median simulated and measured angular spreads were still within 5°.
• The model successfully reproduced the measured statistics of delay spread and angular spread across all four scenarios (28 GHz LOS, 28 GHz NLOS, 140 GHz LOS, 140 GHz NLOS).
• The input parameters listed in Table II (e.g., cluster count, power decay, delay spread, angular spread variances) were sufficient to generate realistic channel impulse responses and angular power spectra.