⚡ electrical engineering

Empirical and Statistical Characterisation of 28 GHz mmWave Propagation in Office Environments

This study empirically characterizes 28 GHz mmWave propagation in office environments using TMYTEK-based measurements, confirming that path loss aligns with free-space theory while revealing that material attenuation varies significantly by type rather than thickness and that reflector optimization can substantially enhance coverage.

Original authors: Ayodeji Bolanle Balogun, Sokipriala Jonah

Published 2026-04-03

📖 4 min read☕ Coffee break read

CC BY 4.0

Original authors: Ayodeji Bolanle Balogun, Sokipriala Jonah

Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). ✨ This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer

Imagine you are trying to send a high-speed message through a crowded office using a super-fast, invisible laser beam (this is what 28 GHz mmWave technology is). You want to know: How far does this beam travel? What happens when it hits a desk or a wall? And can we bounce it off mirrors to reach dead zones?

This paper is like a detective report that answers these questions using real-world experiments and strict math, rather than just guessing. Here is the breakdown in simple terms:

1. The "Laser Beam" in the Office (Path Loss)

The Old Fear: Engineers were worried that inside an office, these fast signals would get messy, bounce off everything, and die out quickly, making them useless for things like VR or 4K streaming.

The Discovery: The researchers set up a test with a transmitter and receiver in a normal office. They found that, surprisingly, the signal behaves almost exactly like a flashlight in an empty room.

The Analogy: Think of the signal as a flashlight beam. In a perfect vacuum, the light gets dimmer at a predictable rate as you walk away. The researchers found that in this office, the signal dims at almost the exact same rate as the flashlight in the empty room.
The Result: They proved mathematically that the signal doesn't get "scrambled" by the office furniture. This means engineers can use simple, reliable rules to design these networks, saving time and money.

2. The "Thick vs. Thin" Wall Myth (Material Penetration)

The Old Assumption: People usually think, "If a wall is thick, it blocks the signal. If it's thin, the signal goes through."

The Discovery: This study proved that thickness doesn't matter as much as what the wall is made of.

The Analogy: Imagine you are trying to shout through two different barriers:
1. A thick, soft foam board (like a display board).
2. A thin, hard plastic partition (like a desk divider).
- You might expect the thick foam to block the sound more. But in this experiment, the thin plastic desk divider actually blocked the signal much more (about 3.4 dB more) than the thick foam board.
The Lesson: It's not about how big the obstacle is; it's about what stuff it's made of. Plastic is a "signal killer," while the fabric-covered wood was surprisingly friendly to the signal. This changes how offices should be designed for Wi-Fi.

3. The "Bouncing Ball" Strategy (Reflectors)

The Problem: Sometimes the signal hits a corner and gets stuck, leaving a "dead zone" where your phone has no internet.

The Discovery: The researchers tried using passive mirrors (reflectors) to bounce the signal around corners.

The Analogy: Imagine playing catch in a room with a pillar in the middle. You can't throw the ball directly to your friend because the pillar is in the way. But if you throw the ball at a wall so it bounces off and hits your friend, the game continues.
The Result: When they used the right angle and shape for the mirror, the signal got significantly stronger (about 2 dB better). However, if the mirror was in the wrong spot or shape, it did nothing.
The Takeaway: You can fix dead zones with mirrors, but you have to aim them perfectly. It's not a magic fix; it requires careful planning.

Why Does This Matter?

Before this study, engineers were flying blind, guessing how these signals would act in offices. They were either being too cautious (wasting money on extra equipment) or too optimistic (risking the network failing).

This paper gives them a reliable map:

Trust the math: The signal acts predictably in open office spaces.
Watch the materials: Don't just look at how thick a wall is; look at what it's made of.
Use mirrors wisely: You can bounce signals around, but you need to aim them right.

In short, this research turns the "mystery" of indoor 5G signals into a clear, predictable science, helping us build faster, more reliable internet for our offices and homes.

1. Problem Statement

While millimeter-wave (mmWave) technology at 28 GHz is critical for beyond-5G systems (supporting AR/VR, IoT, and high-definition streaming), its indoor deployment faces significant challenges.

Knowledge Gaps: There is a scarcity of statistically validated empirical data regarding indoor propagation. Most existing literature is descriptive, lacking rigorous statistical validation (e.g., confidence intervals, hypothesis testing, effect sizes).
Design Risks: Without quantified uncertainty, system designers are forced to adopt overly conservative link margins or optimistic assumptions, leading to inefficient or unreliable network deployments.
Complexity Misconceptions: It is often assumed that indoor mmWave propagation is inherently complex and hostile compared to free-space theory, yet this has not been rigorously proven with statistical evidence in typical office settings.

2. Methodology

The study employed a structured measurement campaign in a typical office environment using TMYTEK Developer Kits (UD Box transmitters, UB Box receivers, and spectrum analyzers) operating at 28 GHz. The methodology focused on three key areas:

Path Loss Characterization:
- Measurements were taken systematically from 10 cm to 100 cm in 10 cm intervals.
- Multiple samples were collected per point to ensure statistical validity.
- Data was fitted to a log-distance path loss model and validated using hypothesis testing, ANOVA, and residual analysis.
Material Penetration Analysis:
- Tests were conducted at four frequencies (26.5, 27.0, 28.0, and 29.0 GHz).
- Two common office materials were compared: Display Boards (8.26 cm plywood with cloth) and Desk Dividers (3.16 cm plastic).
- Statistical comparisons (t-tests, Mann-Whitney U) were used to determine significance and effect sizes.
Coverage Enhancement:
- The study evaluated passive reflectors (X-Rifle) to improve signal strength in non-line-of-sight (NLOS) or constrained scenarios.
- Geometrically optimized reflectors were tested against baseline measurements to quantify signal gain.

3. Key Contributions

The paper makes three primary contributions to the field of mmWave engineering:

Statistically Validated Path Loss Model: Provides a log-distance model with quantified confidence intervals, enabling reliable predictions for system planning.
Material Attenuation Benchmarking: Statistically compares attenuation across common office materials, revealing that material composition is a more critical factor than physical thickness.
Evidence-Based Coverage Enhancement: Demonstrates that optimized passive reflectors can yield statistically significant signal improvements, offering practical solutions for coverage gaps.

4. Key Results

A. Path Loss Modeling

Model Fit: The log-distance model showed an excellent fit ( $R^2 = 0.9901$ , RMSE = 0.62 dB).
Path Loss Exponent ( $n$ ): The estimated exponent was $n = 2.07 \pm 0.073$ .
Theoretical Validation: A hypothesis test confirmed no significant difference between the measured exponent and the theoretical free-space value ( $n=2.0$ ) ( $p = 0.385$ ).
Implication: Short-range indoor mmWave propagation in office environments behaves similarly to free-space propagation, challenging the assumption that indoor environments are inherently complex for these frequencies.

B. Material Penetration Loss

Significant Variance: There was a highly significant difference in attenuation between desk dividers and display boards ( $t = 5.256, p < 0.01$ $t = 5.256, p < 0.01$ ).
- Display Boards: Mean loss = $1.28 \pm 0.82$ dB.
- Desk Dividers: Mean loss = $4.67 \pm 1.00$ dB.
Thickness vs. Composition: Despite being thinner (3.16 cm vs. 8.26 cm), the plastic desk dividers caused 3.4 dB more attenuation than the thicker plywood display boards.
Effect Size: The difference had an exceptionally large effect size (Cohen's $d = 3.717$ ), indicating that material composition dominates attenuation, rendering thickness-based assumptions inadequate for mmWave design.

C. Coverage Enhancement

Passive Reflectors: Optimized reflectors (MS1) provided a mean signal gain of $2.17 \pm 2.33$ dB.
Statistical Significance: The improvement was statistically significant ( $p = 0.048$ ) with a large effect size ( $d = 0.934$ ).
Success Rate: The technique achieved a 57.1% success rate, highlighting the importance of geometric optimization.
Note: Non-optimized beam formation (MS2) did not yield statistically significant improvements ( $p = 0.171$ ).

5. Significance and Engineering Implications

Simplified Design: The confirmation that indoor path loss aligns with free-space theory ( $n \approx 2$ ) allows engineers to use simpler models for short-range deployments, reducing the need for overly conservative link margins.
Material Selection: The findings necessitate a shift in indoor layout planning. Designers must prioritize material composition over thickness when predicting signal blockage. Thin plastic dividers can be more detrimental than thick wooden boards.
Quantified Uncertainty: By providing 95% confidence intervals (e.g., for path loss exponent and material attenuation), the study enables precise risk assessment and link budget calculations.
Practical Deployment: The study validates the use of passive reflectors as a cost-effective method for coverage enhancement, provided they are geometrically optimized based on site-specific surveys.

In conclusion, this paper bridges the gap between academic research and commercial application by establishing a statistically rigorous framework for 28 GHz indoor propagation, moving beyond descriptive studies to evidence-based engineering.