Indoor Radio Propagation Model Research Articles

EM DeepRay: An Expedient, Generalizable, and Realistic Data-Driven Indoor Propagation Model

Efficient and realistic indoor radio propagation modeling tools are inextricably intertwined with the design and operation of next-generation wireless networks. Machine-learning (ML)-based radio propagation models can be trained with simulated or real-world data to provide accurate estimates of wireless channel characteristics in a computationally efficient way. However, most of the existing research works on the ML-based propagation models focus on outdoor propagation modeling, while indoor data-driven propagation models remain site-specific with limited scalability. In this article, we present an efficient and credible ML-based radio propagation modeling framework for indoor environments. Specifically, we demonstrate how a convolutional encoder–decoder can be trained to replicate the results of a ray tracer, by encoding physics-based information of an indoor environment, such as the permittivity of the walls, and decoding it as the path loss (PL) heatmap for an environment of interest. Our model is trained over multiple indoor geometries and frequency bands, and it can eventually predict the PL for unknown indoor geometries and frequency bands within a few milliseconds. In addition, we illustrate how the concept of transfer learning can be leveraged to calibrate our model by adjusting its preestimate weights, allowing it to make predictions that are consistent with measurement data.

Millimeter Wave and Sub-THz Indoor Radio Propagation Channel Measurements, Models, and Comparisons in an Office Environment

This letter provides a comparison of indoor radio propagation measurements and corresponding channel statistics at 28, 73, and 140 GHz, based on extensive measurements from 2014-2020 in an indoor office environment. Side-by-side comparisons of propagation characteristics (e.g., large-scale path loss and multipath time dispersion) across a wide range of frequencies from the low millimeter wave band of 28 GHz to the sub-THz band of 140 GHz illustrate the key similarities and differences in indoor wireless channels. The measurements and models show remarkably similar path loss exponents over frequencies in both line-of-sight (LOS) and non-LOS (NLOS) scenarios, when using a one meter free space reference distance, while the multipath time dispersion becomes smaller at higher frequencies. The 3GPP indoor channel model overestimates the large-scale path loss and has unrealistic large numbers of clusters and multipath components per cluster compared to the measured channel statistics in this letter.

Bringing It Indoors: A Review of Narrowband Radio Propagation Modeling for Enclosed Spaces

Small cells are now widely deployed indoors to address hot-spot areas where capacity uplift is needed. This deployment leads to the increase of wireless networks as a challenge to service demands of personal communication systems, which has inspired the scientific community to work towards understanding and predicting in-building radio wave propagation performance. Despite this, only a few reviews have attempted to overview channel modeling for specific indoor environments and even fewer outline remarks that include a methodology for designing and planning indoor radio systems. Consequently, a comprehensive survey of indoor narrowband channel models is presented, spanning more than 30 years of continuous research to overview and contrast significant developments including their disadvantages, and proposing a new taxonomy to analyze them. Finally, remarks on indoor radio propagation modeling with a vision for future research opportunities are presented.

Unmanned Aerial Vehicle-to-Wearables (UAV2W) Indoor Radio Propagation Channel Measurements and Modeling

In this paper, off-body ultra-wide band (UWB) channel characterization and modeling are presented between an unmanned aerial vehicle (UAV) and a human subject. The wearable antenna was patched at nine different body locations on a human subject during the experiment campaign. The prime objective of this work was to study and evaluate the distance and frequency dependent path loss factors for different bandwidths corresponding to various carrier frequencies, and also look into the time dispersion properties of such unmanned aerial vehicle-to-wearables (UAV2W) system. The environment under consideration was an indoor warehouse with highly conductive metallic walls and roof. Best fit statistical analysis using Akaike Information Criteria revealed that the Log-normal distribution is the best fit distribution to model the UWB fading statistics. The study in this paper will set up a road map for future UAV2W studies to develop enhanced retail and remote health-care monitoring/diagnostic systems.

MapFuse: Complete and Realistic 3D Modelling

Validating a 3D indoor radio propagation model that simulates the signal strength of a wireless device can be a challenging task due to an incomplete or a faulty environment model. In this paper, we present a novel method to simulate a complete indoor environment that can be used for evaluating a radio propagation model efficiently. In order to obtain a realistic and robust model of the full environment, the OctoMap framework is applied. The system combines the result of a SLAM algorithm and secondly a simple initial model of the same environment in a probabilistic way. Due to this approach, sensor noise and accumulated registration errors are minimised. Furthermore, in this article, we evaluate the merging approach with two SLAM algorithms, three vision sensors, and four datasets, of which one is publicly available. As a result, we have created a complete volumetric model by merging an initial model of the environment with the result of RGB-D SLAM based on real sensor measurements.

A Map-Assisted WiFi AP Placement Algorithm Enabling Mobile Device’s Indoor Positioning

Location information and positioning technology are important to some Internet of Things (IoT) applications. The accuracy of indoor positioning using WiFi can be substantially enhanced by appropriate access point (AP) placement strategies, i.e., in a given indoor environment to deploy the WiFi APs at the locations where the mobile devices can work out their location more precisely. The plan of AP placement needs to be generated automatically by algorithms, especially for large-scale indoor environment. This paper presents an indoor map system that provides coordinate system and graphic representation. The detailed map information such as walls can be explicitly expressed and used to assist the AP placement algorithm. In this paper, AP placement is formulated into an optimization problem in which the sum of Euclidean distance of fingerprints among all the reference points (RPs) is maximized. The fingerprint at RP is predicted by an indoor radio propagation model which takes the attenuation of walls into consideration with the assistance of our indoor map. The optimization problem is solved by particle swarm optimization (PSO) and evaluated by k-nearest neighbors positioning algorithm in a real-world environment. The experimental results show that our map-assisted AP placement can provide higher positioning accuracy.

An indoor radio propagation model considering angles for WLAN infrastructures

AbstractWireless local area network fingerprint‐based indoor location system is a hot topic these years because it needs no extra hardware and is very easy to deploy. However, it demands a database containing the distribution of received signal strength (RSS) of the area of interest,called radio map. Conventionally, we need to grid the area densely and manually measure RSS values on intersections, which will consume a lot of time and human resources. What is worse, change of the environment may render this database totally useless. Our consideration is to measure RSS on a small amount of these intersections and use them to build a radio propagation model. Then, this model can be deployed to predict RSS values of other intersections and reconstruct the radio map. In other words, we only need to collect a very small part the radio map and utilize the radio propagation model to recover the whole one. So far, many models have been proposed, among which the one suggested by Seidel, named floor attenuation factor propagation model, achieves great balance between computational request and accuracy. But it is not compatible with environments in some scenarios. So as to compensate for this deficiency, we take into account the angles formed by signal and surfaces of obstacles, and the results show better compatibility. The proposed model has four parameters that are related to the environments, and our second contribution in this paper is to propose a method to determine them. In fact, after collecting a small part of the radio map, we can estimate these parameters with least square method. Then, these parameters can be used to predict the signal strength at any other points in the same environment, and the whole radio map is rebuilt. According to practical experiments, performance of the radio map built by the proposed model is not as good as the manually collected one, but 80% of collecting labor is saved. Copyright © 2015 John Wiley & Sons, Ltd.

Study on the Propagation Characteristics of Radio Wave for Indoor Non-Line-of-Sight

The propagation characteristics of radio wave have been an important topic in wireless communications. Based on the ray tracing method, the propagation of radio wave for indoor NLOS environment is simulated and analyzed. In this paper, the received power is obtained by simulation, and we will analyze the impact of various factors on the received power. Later, the study can be used to simplify indoor radio wave propagation model and provide a theoretical basis, which is in favor of indoor wireless communication network planning and optimization and can lay the foundation of the development of future technology.

MineLoc — Personnel Tracking System for Longwall Coal Mining Sites

The localization of people and objects in indoor environments is an ongoing research challenge with a diverse set of possible positioning sensors. For the harsh environment of an underground coal mine, a system relying on received signal strength (RSS) measurements of common radio modules has been proven to deliver accurate and reliable positioning results. However, in tunnel environments of a longwall mining facility, conventional indoor radio propagation models are not valid due to waveguide effects. Additional investigations regarding the RSS-based ranging and the localization algorithm will be proposed. Ray tracing is used to find an appropriate propagation model and to define suitable range sections for different radio frequency bands. Simulation and experiment ranging results are compared for 2.4 GHz and sub- GHz radios. An enhanced weighted centroid localization (WCL) approach is essential, taking into account the peculiarities of the longwall mining environment.

Research indoor radio propagation models for design survivability security systems built on the ZIGBEE standard

In this article describes the main types of radio propagationmodels and expediency of the application of thesemodels for the simulation is substantiated. The knownindoor radio propagation models are considered, that is:OSM (one-slope model), model Keenan-Motley, COST231 Multi-Wall Model. The theoretical calculations basedon these models are conducted. The method and meansof experimental research radio propagation of ZigBeestandard are described. The results of experimental researchwas conducted and have been compared with theoreticalcalculations of the signal attenuation. The combinedresults of the research are processed and analyzed.The suitability of known models for the design of a wirelesssecurity system, built on the standard ZigBee is verified.A new approach for the design and simulation ofwireless systems, which can improve their characteristicssuch as reliability and survivability was proposed.

Dynamic 3-D Indoor Radio Propagation Model and Applications with Radios from 433 MHZ to 2.4 GHz

Proliferation of indoor sensor infrastructure has created a new niche for mobile communications, yet research in indoor radio propagation still has not generated a definite model that is able to 1) precisely capture radio signatures in 3-D environments and 2) effectively apply to radios at a wide range of frequency bands. This paper first introduces the impact of wall obstructions on indoor radio propagation by experimental results through a full cycle of an indoor construction process; it then exploits a dynamic 3-D indoor radio propagation model in a two-story building using radio technologies at both 433 MHz and 2.4 GHz. Experimental measurements and evaluation results show that the proposed 3-D model generates accurate signal strength values at all data evaluation positions. Comparing the two radio technologies, this study also indicates that low frequency radios (such as 433 MHz) might not be attractive for indoor mobile computing applications because of larger experimental errors or constant absence of measurement data.

Indoor Radio Propagation Model Based on Dominant Path

When there are bigger obstacles in the indoor environment such as elevator, the radio waves basically can not penetrate it. The contribution of received signal strength by transmission and reflection will be greatly reduced, and most of the time, the radio waves will reach the user by bypass diffraction. Therefore, the traditional path loss model is no longer applicable, and the improved model should be proposed. In this paper, we firstly proposed an indoor radio propagation model based on dominant path in which the received signal strength has nothing to do with the direct distance between user and access point, but is related to the length of dominant path. Then on the basis of dominant path model, the NLOS influence is considered in order to further improve the accuracy of dominant path model. Experimental results demonstrated that the proposed dominant path model can improve the accuracy of traditional path loss model remarkably.

Programming an Artificial Neural Network Tool for Spatial Interpolation in GIS - A Case Study for Indoor Radio Wave Propagation of WLAN.

Wireless communication networks offer subscribers the possibilities of free mobility and access to information anywhere at any time. Therefore, electromagnetic coverage calculations are important for wireless mobile communication systems, especially in Wireless Local Area Networks (WLANs). Before any propagation computation is performed, modeling of indoor radio wave propagation needs accurate geographical information in order to avoid the interruption of data transmissions. Geographic Information Systems (GIS) and spatial interpolation techniques are very efficient for performing indoor radio wave propagation modeling. This paper describes the spatial interpolation of electromagnetic field measurements using a feed-forward back-propagation neural network programmed as a tool in GIS. The accuracy of Artificial Neural Networks (ANN) and geostatistical Kriging were compared by adjusting procedures. The feedforward back-propagation ANN provides adequate accuracy for spatial interpolation, but the predictions of Kriging interpolation are more accurate than the selected ANN. The proposed GIS ensures indoor radio wave propagation model and electromagnetic coverage, the number, position and transmitter power of access points and electromagnetic radiation level. Pollution analysis in a given propagation environment was done and it was demonstrated that WLAN (2.4 GHz) electromagnetic coverage does not lead to any electromagnetic pollution due to the low power levels used. Example interpolated electromagnetic field values for WLAN system in a building of Yildiz Technical University, Turkey, were generated using the selected network architectures to illustrate the results with an ANN.

A Conducting Cylinder for Modeling Human Body Presence in Indoor Propagation Channel

We demonstrate that in indoor radio propagation modeling, the presence of the human body may be approximated by a conducting circular cylinder at microwave frequencies. Therefore, a perfect tool such as the uniform theory of diffraction may be used to predict the diffracted field over a smooth circular surface. To validate the model, vertically and horizontally polarized continuous wave (CW) measurements were performed at 10.5 GHz between two fixed terminals inside a room along with the presence of an obstacle (person or metallic cylinder) moving along predetermined parallel and perpendicularly crossing paths with respect to the line-of-sight direction. Results indicate that there is a strong correlation between the effects of the human body and those of a conducting circular cylinder. The simulation results successfully agree with the CW experimental measurements.

Accuracy evaluation analysis for indoor measurement-based radio-wave-propagation predictions

An accuracy evaluation analysis of in-building path loss prediction models is presented, comparing the performance of measurement-based prediction against traditional indoor radio propagation models, such as Keenan–Motley, tuned with measurements. The analysis was conducted using extensive walk test data from various antennas at 1800 MHz collected in two types of buildings: an old Victorian manor-house built from brick and a modern purpose-built office building with open-plan construction. The measured data were split into two parts: a tuning set and an evaluation set, such that the data used to run the measurement-based prediction were excluded from the data used for the accuracy evaluation analysis. The results show a significant improvement in the prediction accuracy for the indoor measurement-based model over the tuned Keenan–Motley model.

Uplink Power Control in Bluetooth Transceiver

ABSTRACT In this paper, a new method that controls the uplink transmit power in Bluetooth transceiver is suggested. Two closed loop power control (CLPC) algorithms are proposed. One is the fixed step power control (FSPC). The other is the dynamic step power control (DSPC). The proposed power control algorithms are simulated under indoor radio propagation model. Simulation results show that power consumption of Bluetooth devices is reduced using the proposed power control algorithms.