In: Exhibitions, Press releases 18 May 2017 Tags: , , , , ,

Human and Field: Submission or Interaction/ ATDI and CAS WUT Symposium (STERDYŃ 19-21 MAY 2017)


The deployment of different sources of electromagnetic fields (EMF) to cater for the telecommunication and ICT needs of urban and rural communities has developed very rapidly. This has been due to strong competition, ongoing traffic growth, quality-of-service requirements, network coverage extension and the introduction of new technologies. It has prompted concern on the possible effects of prolonged exposure on people’s health. The growing concern in some countries about electromagnetic field exposure from antenna towers has led to imposition of new legislation and/or regulations, to ensure protection of the public health. Public concern about possible health hazards due to continued exposure to EMF has become a significant issue for regulators and service providers in some markets. The regulation of non-ionizing radiations contains exposure standards and emission standards. The exposure standards are specifications that limit the exposure of people to the electromagnetic fields, and the emission standards are specifications that limit the emission of electromagnetic fields from the devices. The EMF assessment methods depend on site and environment; calculations are suitable in many cases and have significant benefits (accurate, fast and cost effective), whereas measurements are usually only required in very complex environments. Field monitoring is effective for the safety of workers when working on towers. While, field surveys can provide public reassurance, continuous monitoring has limited long term benefit, when electromagnetic fields levels are low and stable. The ITU estimates that seven billion people (95 per cent of the global population) live in an area that is covered by a mobile-cellular network. Mobile-broadband networks (3G or above) reach 84 per cent of the global population but only 67 per cent of the rural population. The electromagnetic fields are undetectable by people, and the lack of communication and information to citizens can generate a lack of trust, which may become fear. Global technical standards can help facilitate compliance with international exposure guidelines, strengthen collaboration among stakeholders, ensure transparency, and promote communication with citizens. In 2009, the International Commission on Non-Ionizing Radiation Protection (ICNIRP) reconfirmed its 1998 radio frequency “guidelines on limiting exposure to high and radiofrequency fields in the range (100 kHz–300 GHz).” The World Health Organization (WHO) is developing an update of the Environment Health Criteria (EHC) monograph on radiofrequency fields. The current position of the WHO is that the ICNIRP guidelines provide protection for all persons from all established health hazards. However, there are gaps in scientific knowledge and research is on-going. Above a certain threshold exposure level, the absorption of radiofrequency (RF) EMF energy by the body or a part of the body results in a rise in body temperature. The absorption of RF is measured in terms of the Specific Absorption Rate (SAR). The SAR limits are set with a safety margin, below the threshold level at which the body temperature starts to rise. The human body is efficient at maintaining its temperature and has sophisticated mechanisms to prevent the temperature from rising when heat is absorbed from any source, as demonstrated by our ability to live in varying climatic conditions from cold to hot all around the world. Around the world, the use of mobile phones and other wireless systems is expanding rapidly. While this provides the opportunity for advances in public and personal safety, education, medicine and the economy, it also brings new responsibilities and challenges for local authorities. In particular, there have been some concerns, that along with the benefits brought by wireless networks, there may also be risks to health.
Dr. Haim Mazar ATDI, Spectrum Management and Engineering, Vice Chair ITU-R Study Group 5 (terrestrial services)


Jack Rowley – Senior Director Research & Sustainability, GSMA
Abstract: Cellular mobile networks rely on continuous coverage from mobile network antennas sites to provide connectivity to portable devices. The radio connection between the fixed antenna sites and the mobile device is constantly monitored and the output power adjusted to maintain the target communication service, initially voice but increasingly now data. Any person using a mobile or portable telecommunications device is exposed to the radiofrequency electromagnetic fields (RF-EMF) that are transmitted by the device and network antennas. These RF-EMF transmissions are necessary to convey the communication signals (voice or data) between the device and its corresponding wireless network. This paper will review existing research on the relative radiofrequency (RF) exposure levels and factors that influence exposures for both fixed and mobile sources. Both sources typically result in exposure levels that are a small fraction of international RF exposure guidelines. For example, mobile devices typically operate at about 1% of their maximum power [1, 2] and the mean environmental RF levels from cellular mobile communications systems are typically less than 0.1 μW/cm2 (the international public limit is 450 μW/cm2 at 900 MHz) [3].In some countries misunderstanding by the public and policy makers has been associated with the adoption of policies that cause inefficient deployment of cellular services. Scientifically based policy for the siting of antennas is associated with lower levels of public concern and more efficient antenna deployment. Some good practice policy recommendations are proposed based on evidence and practical experience.

Haim Mazar – RF Spectrum and Engineering ITU Expert Vice Chair of ITU-R Study Group 5
Abstract: Compliance with human exposure limits for electromagnetic fields (EMFs) is a significant health and safety issue to regulators, service providers and wireless equipment suppliers. The recent exposure limits are reported. In addition to WHO, IEEE and ICNIRP, following the ITU Plenipotentiary Conference in 2014 (PP14) Resolution 176 on “Human exposure to and measurement of electromagnetic fields”, ITU-R, D and T are most active to regulate and standardise the radio aspects of the EMF. The Specific Absorption Rate (SAR) and the power-density (PD) reference levels in European countries, USA, Canada, China, Japan and Korea are compared and contrasted. The allowed SAR cellular handsets’ exposure limits for localized heating are more restrictive in the USA, Canada and Korea (1.6 W/kg), relative to others (2 W/kg). Even the averaging is more restrictive: averaged over 1 g in N. America and Korea, versus 10 g tissue in ICNIRP 1998 and ANSI/IEEE C95.1-2006. Europe in general follows the ICNIRP 1998 PD levels from base stations. Despite the (non-mandatory) EU Council Recommendation 1999/519/EC, some EU countries adopt more restrictive thresholds. USA and Japan are the most liberal countries, adopting in 300–1,500 MHz power- density 4/3 of the ICNIRP1998 and IEEE 2006 levels. On 13 March 2015, Health Canada revised the 2009 PD limits (that were identical to the USA) and published more restrictive reference levels. There is no scientific reason to use different exposure limits in different countries. Some explanations of the different limits are provided.

Sébastien Grimoud – Engineer specialized in spectrum management
Abstract: The potential health risks of radiofrequency electromagnetic fields (RF EMFs) emitted by cellular networks (GSM, UMTS, Wifi…) are currently of considerable public interest. A very important issue is the requirement for coexistence between wireless equipment and people living around those types of transmitters. In the last few years a noticeable acceleration in the activities related to the technical standards in the area of the human exposure of electromagnetic fields has been investigated at international, European and national levels. Notifications have been specified by the European Union to the regulation authorities and cellular operators in the Europe union community (IEEE standard 95.1-11999). The purpose of those recommendations was to take into account the potential health risk especially when the antennas used by the operators are located in urban areas (usually located on rooftops) and when they are close to sensitive areas like hospital, schools, people living near by the RF transmitters… Today, the observance of existing EMF maximum permissible levels (standards) is mandatory for all base station equipment installations. • The maximum permissible exposure (MPE) in a frequency range from 10kHz to 300GHz. • The area of exposition risk where the field strength is higher than the acceptable level (in outdoor or indoor environment). • All the EMF (electromagnetic fields) sources with different frequencies and different modulations. • Full access to clear and accurate information about EMF emitting sources.


Human and Field: Submission or Interaction/ ATDI and CAS WUT Symposium Program

Harmonogram/Program of the Symposium

19 maja 2017/ 19th of May 2017


Wyjazd z Warszawy/ Departure from Warsaw


Przyjazd/Arrival  to Sterdyń




Rozpoczęcie Sympozjum/ Inauguration


Dyskusja Panelowa/Podium Discussion



20 maja 2017/ 20th of May 2017



9:30- 9:50

Molecular dissociation with low frequency electromagnetic radiation

Dr. Krzysztof Kempa, Department of Physics, Boston College, USA


Modern IEEE 802.11 standards and their impact on the electromagnetic environment in highly urbanized areas

Prof. Zbigniew Piotrowski, Telecommunications at Military University of Technology (MUT), Poland


ATDI calculation method to identify high field strength exposure hot points at few meters precision

MSc. Eng. Sébastien Grimoud, Ingénieur spécialiste de la gestion du spectre, France


Coffee Break


Factors affecting radiofrequency (RF) exposure levels from mobile devices and network antennas

Dr. Jack Rowley, Senior Director Research & Sustainability, GSMA


Sub-wavelength anti-reflection coatings for THz and millimeter wave region

MSc. Artur Sobczyk, Faculty of Physics, Warsaw University of Technology


Thermal effects in tissues exposed on high frequency electromagnetic wave – 3D simulator results comparisons

Dr. Eng. Grzegorz Domański, MSc. Eng. Michał Wieteska, Institute of Radioelectronics and Multimedia Technology, Warsaw University of Technology



14:00-14: 20

In-vivo effects of tissue electromagnetic exposure by means of Magnetic Resonance Imaging

Prof. Piotr Bogorodzki, Institute of Radioelectronics and Multimedia Technology, Warsaw University of Technology


Remarks on quantum and structural approach to the interaction of electromagnetic signals with living systems

Prof. Michał Urbański, Faculty of Physics, Warsaw University of Technology


Coffee Break


The importance of electromagnetic fields’ affect in the context of location sites intended for permanent people’s stay

MSc Marianna Ulanicka, Faculty of Geodesy and Cartography, Warsaw University of Technology


Effects of Electromagnetic Field Emitted by Cellular Phones

Prof. Michael Giersig, Department of Physics, Freie University Berlin


Multiscale Approach to Neural Tissue Modelling

Prof. Jacek Starzyński, Institute of Theory of Electrical Engineering, Measurement and Information Systems, Faculty of Electrical Engineering, Warsaw University of Technology

19:00 -21:00

Kolacja Uroczysta/Dinner


Zajęcia wieczorne/ Activities

21 maja 2017/ 21st of May 2017




Human Radio Frequency Exposure Limits: ITU activities and reference levels in Europe, USA, Canada, China, Japan and Korea

Dr. Haim Mazar, RF Spectrum and Engineering ITU Expert, Vice Chair of ITU-R Study Group 5


Nanostructures for Bioelectromagnetism: Sensing, Stimulation, and Demodulation

Prof. Michael J. Naughton, Department of Physics, Boston College (USA)

10:10 -10:30

Nanocomposite for efficient sub-terahertz radiation protection

MSc. Anna Łapińska, Faculty of Physics, Warsaw University of Technology


Podsumowanie/Conclusion remarks






ATDI_ Interference


Press release:,nId,2394719,zyjemy-wsrod-fal-czy-mamy-sie-czego-obawiac

Żyjemy wśród fal – czy mamy się czego obawiać?

Żyjemy wśród fal – czy mamy się czego obawiać?

Human and Field: Submission or Interaction | Debata na temat w wpływu fal radiowych na organizm człowieka


Jak fale radiowe wpływają na człowieka?

In: Products, Resources 15 May 2017 Tags: , , , , , , , ,

Efficiently planning mesh networks with HTZ (Part 1 – Digital cartography).

This post is intended to help a radio-planner, technical director, project manager, or consultant to be more aware of the important goals to pursue when planning large scale mesh networks in urban environments. It proposes innovative ways to accurately manage large areas of interest, using cartographic data with mixed high and medium resolutions.


The radio-planning of mesh networks can be divided into three main topics: – Dimensioning the mesh node distribution in order to achieve the requirement of coverage of the end user. – Analyzing the linkage of the Mesh Nodes, in order to optimize the dynamic routing and therefore ensuring demand throughput. – Backhauling the gateways (Microwave links…).

  • Required components
    Cartographic data Mesh network planning can be achieved by using different kinds of digital cartography. The choice depends on the data already available, the budget to be spent, the time available for the planning and the accuracy to reach. The user usually is able make the choice between two types of datasets: – Medium Resolution cartography – High Resolution cartography giving exact locations and heights of the buildings for a given area of interest. However, both datasets have their pros and cons because the areas to treat during mesh planning are large. A third dataset choice known as a hybrid dataset, combines the advantages of both other types of cartography and will be highlighted throughout this document.


Medium Resolution for large areas (From 10 to 30 m resolution)
A typical medium cartographic dataset contains the following layers:

– A Digital Terrain Model

– A clutter file, provides a description of the ground occupancy as major aggregates (urban, dense urban…)

– Topographic or Aerial maps (Online or Offline)


Adapting the medium cartography to mesh planning Standard Medium Resolution datasets usually do not feature the roads, because their width is usually smaller than the resolution of the dataset itself. Roads and streets are a crucial component for mesh radio-planning.  The mesh nodes are usually installed in the streets in order to take advantage of the canyoning effect. If the roads and the streets are not available, HTZ features a drawing interface allowing the radioplanners to add the streets in clutter file by importing the street network from a GIS database (OSM, National Geoportal, GIS collections…)


Pros and Cons

The Medium Resolution dataset for mesh planning offers several advantages:

– It allows the treatment of very large areas: the planning of an entire large city can easily be achieved

– The availability of this data is quite good, usually for a reasonable cost

– The resolution of the data allows very fast computations

– Prediction values can be compared with mobile measurement data

However, the radio-planner has to keep in mind that a reduced resolution for the cartography usually generates a reduction in the planning accuracy. Because of the sensitivity to the building environment of the mesh frequency (usually in the ISM bands), using a coarse cartography will generate a coarse planning result that might not reflect the planning accuracy that is targeted (especially for the “hot-zone(s)). Also, the cartography must be manually treated in order to “dig” the streets in the dataset (if the data is not already available in GIS format), in order to provide the ability to simulate the canyoning effect between the mesh nodes.

Availilbity: Worldwide (<=30 m)

Planning accuracy (standard deviation):

– HTZ (Deygout94 propagation model): <=5 dB

– Empirical propagation models (3GPP / Seamcat / Cost): <=8 dB

– Half determinitistic models (ITU / FCC): <= 7 dB

– Coordination models (ITU / HCM): <= 10 dB

Cost-effectivness (Dataset building workload): < 2 days (depends on surface and resolution)

Vintage dependency (Free Clutter data): between 5 and 10 years old


High Resolution (from 1 m to 5 m)

A typical high resolution cartographic dataset contains the following layers:

– A high resolution Digital Terrain Model (featuring the bridges for instance)

– A building height file, for the canyoning effect and for building diffusion loss

– A clutter file that describes the vegetation and the different “types” of buildings (concrete, glass…)

– Ortho-photos or Aerials


Pros and Cons

High Resolution cartographic data provides precise building location and height for a specified area of interest. It is the optimal product to achieve excellent planning accuracy in outdoor (canyoning effect according to the exact shape of the buildings) and also in indoor (signal diffusion according to the building type) environments, even though it might require longer computation time.

– Prediction values cannot be compared with mobile measurement data (only fixed measurement data)

However, this type of data remains expensive. It is therefore advised to be used on small areas, and centred, for instance, on “hot-zone(s)”. The coverage calculated also depends on the building data available: the vintage of the production source is also quite important.


Availilbity: low but can be built on demand (around 150 EUR/km²). Some geographical institutes offer HR data for free or at a very attractive price (< 20 EUR/km²)

Planning accuracy (standard deviation):

– HTZ (Deygout94 propagation model): <=4 dB

– Empirical propagation models (3GPP / Seamcat / Cost): <=8 dB

– Half determinitistic models (ITU / FCC): <= 6 dB

– Coordination models (ITU / HCM): <= 10 dB


Hybrid cartographic dataset

Another option in preparing a workspace for the planning of a WiFi mesh network would be a hybrid cartographic dataset. The hybrid dataset uses medium resolution data for the areas where a high degree of simulation accuracy is not critical. The hybrid dataset uses high resolution data for “hotspots” within the user’s planning workspace to optimize simulation accuracy for critical areas. High resolution data includes exact building dimensions centred over these “hotspots.”

The hybrid dataset contains both medium and high resolution layers of cartographic information:

– The DTM covering the entire Area Of Interest, with more details in the hot-zone

– A Clutter file mixing the Medium Resolution data and some High Resolution data

– A building height layer covering the High Resolution areas only (the urban heights in the Medium Resolution are managed in the clutter file)

– Imagery (Online or Offline)

– Vector layer (3D building polygons, transportation…)



Pros and Cons

The hybrid dataset combines the assets of the two datasets previously defined. For most areas, coarse radioplanning is performed with both time and cost effectiveness, whereas the “hot-zones” can be locally analyzed with high planning accuracy. The clutter file requires a careful configuration, because it mixes medium and high resolution data:

– The medium resolution clutter codes are configured with average heights, that will be used by the NLOS (diffraction) engine of HTZ when the final receiver is located inside these clutter codes (Suburban for instance)

– The high resolution clutter codes are configured with no heights (as they are defined in the building height file), but with a diffusion loss coefficient in dB/km. This will be used when the final receiver will be located in a building in a “hot-zone”.




High Resolution Terrain & Clutter Datasets: Why Lidar?
There are myriad methods, techniques and technologies for obtaining elevation and earth cover information through propagated signals. Those technologies may be based on sound, radio and light and also vary in resolution, difficulty, expense and process. Overall, most of these sensing technologies are based on the time delay of a reflected or scattered signal, though traditional passive sensors can also be used and rely on natural radiation.
Lidar systems illuminate a target with lasers, then receive and process the reflected and/or scattered signal. Modern Lidar systems are compact, precise, and efficient and provide many advantages over traditional photo-based techniques. They allow for sub-1 meter data collection and improvements in post-processing aid in the ease of use of the data. Most post-processed Lidar data is classified by return number and category, further shortening the conversion process from raw data to datasets that are usable in RF propagation tools.
Another advantage of Lidar data collection is that the data may be collected both day and night unlike traditional methods which require collection during daylight. Lidar not only offers high accuracy, but allows for the collection of elevation information in areas of dense vegetation. Since a Lidar pulse can have multiple reflections, it will reveal both surface elevation and terrain elevation at any point. Most other collection techniques only gather information about surface heights. Furthermore, modern Lidar data collection systems are compact and are easily mounted onto light aircraft for data collection over large areas.

Get Lidar Data
Lidar, or light detection and ranging, can be used to quantize terrain, ground clutter and ground occupancy. Airborne Lidar systems are typically used for the purposes of scanning large areas and are composed of a laser and a rotating mirror that is used to sweep the area of interest. The airborne Lidar system then acquires data points by bouncing a laser signal off of the earth, buildings and vegetation. As the airplane flies, the Lidar system quantizes the terrain and ground clutter below in a zigzag pattern, as pictured below.


The acquired data points are reflections of the laser signal from obstacles in its path, and there may often be multiple reflections of a single emitted signal. One reflection may be produced by buildings, the ground and other solid objects. Trees and vegetation may produce several reflections as the laser signal propagates through the leaves and reflects off of branches and ultimately the ground. Thus, it is common to have multiple returns for a given transmission.
To compute the distances between the airborne Lidar sensor and the reflection point and thus the elevation of the reflection point, calculations are run using the elapsed time and the speed of light. This data is correlated with the GPS positioning of the aircraft along with inertia sensors or gyroscopes to accurately create the environment of three dimensional points that are a Lidar dataset.

Lidar Data Format
Lidar information is typically obtained and stored in ASPRS LAS format. Not only does the LAS format contain information about surface heights, but it also provides header information that contains technical information such as return number, classification, and scan angle, among others. The user may then employ or develop software that sorts through the Lidar data (often in the realm of Gigabytes of data) to create the desired datasets based on required criteria, such as return number or classification.
Once the Lidar data has been sorted as desired, the data can then be manipulated as necessary. In most cases, this involves interpolation of the dataset to create a continuous model without non-return pixels. Lidar data is, by nature, discontinuous since individual measurements are based on specific geographic points. These points are then stored in the LAS file. In essence, a LAS file is a list of measurement information per geographic point. In Figure 2 the image on the left shows a dataset where only the first return is shown.  Any areas in black are points where Lidar data was not obtained during the measurement campaign.  In the image on the right, the dataset is interpolated into a continuous dataset that can be used in radio frequency planning and analysis software as a digital surface model.


Lidar Dataset Preparation for RF Analysis

The images in Figure 3 and descriptions that follow show how ground occupancy and clutter are generated using processed Lidar data:
Aerial Image: The first image is an aerial photo of the area of interest, showing the presence of roads, vegetation, buildings and unoccupied ground.
Bare Earth Image: The second image is a bare earth model that was extracted from the ground points of a Lidar dataset and then interpolated into a smooth, continuous dataset. The bare earth model is also known as the DTM, or digital terrain model, since it contains only ground elevations. The DTM is derived from a Lidar dataset by removing all points but those classified as ground points and then interpolating the data to create a continuous dataset.


First Return Image: The third image is a first return model that was extracted and then interpolated into a smooth, continuous dataset. The first return model may also be called a DSM, or digital surface model, since the heights and elevations it contains are the maximum elevations for the ground and any ground clutter at each point. The DSM is derived from a Lidar dataset by removing all returns but the first return and then interpolating the data to create a continuous dataset.
Ground Occupancy Image: The final image is a clutter dataset, obtained by subtracting the heights in the digital terrain model from the heights in the digital surface model, leaving only buildings, vegetation and any other ground clutter within the file.

Areas in black represent a lack of clutter, where the digital elevation model and the digital surface model are equivalent.


RF Analysis Using Lidar Data

Once the Lidar data is processed and converted to the appropriate formats, the user may load the datasets into HTZ to run simulations.

The high resolution Lidar dataset provides for highly precise modeling with sharp blockages.


The above image, is a three dimensional visualization of how the sample RF signal is incident upon the exterior of a large building.  The color variation across the building’s facade and stepped roof represents varying power received levels of the RF signal.

The Case for Lidar Datasets

While traditional terrain and surface cover collection techniques and technologies yield resolutions that often range in the tens of meters and can be as accurate as 3 to 5 meters, Lidar allows for sub-1 meter data collection. As a highly precise and detailed terrain and clutter format, Lidar data is well suited for high-resolution RF analysis. Not only is the user presented with unparalleled accuracy for propagation over bare terrain, but also for propagation over and through ground clutter.

In: Products, Resources 13 May 2017 Tags: , , , , ,

MF Groundwave Propagation Modeling for Maritime Networks
Introduction to modeling MF band propagation (3 kHz – 30 MHz) for Maritime Networks with HTZ
For the past seventeen years ATDI has been integrating and developing software for modeling anomalous radio wave propagation for the purposes of RF network design. This includes propagation phenomenon such as ducting, troposcatter and their applications over terrain and water.
Over the past five years, ATDI has dedicated significant resources into investigating how to model the propagation characteristics of frequencies below the VHF band. There are many applications to these frequencies including but not limited to:

  • Aeronautical Navigational Aids
  • Automatic Link Establishment for Intelligence gathering
  • Emergency communications for Maritime Networks


ATDI has developed several specific features into its product line for modeling a variety of below VHF band propagation for each of these applications, this document will be the first in a three-part series highlighting how ATDI’s flagship RF network design tools model Maritime Communications.
This first document will focus on modeling MF Groundwave propagation from ship to shore along coastlines. This paper will focus on developments in the areas of cartographic map data preparation, integration of propagation standards and calibration information and custom reporting options available to users of HTZ for the purposes of modeling Maritime Networks.


Preparation of a Conductivity/Permittivity Map from the ITU IDWM database:

In the case of MF propagation, terrain obstruction information provided by the classic Digital Terrain Model used with most RF network modeling packages is of greatly diminished importance. More important, are the electromagnetic properties of the terrain in particular the Conductivity and Permittivity of the ground.
These types of maps are usually available from the local national spectrum authority. ATDI’s GIS management tool, ICS map server tool can create these maps from any type of source (digitized map, vector map, etc.) in a format compatible for RF analysis with HTZ.
ATDI cartographic services can also provide this type of information for any country in the world using the ITU Digital World Map (IDWM) database as a global source of conductivity and permittivity data in all varying regions. Note, that this is the same source for the conductivity map in the FCC 47 CFR 73.190.

The map above is provided in the form of HTZ’s classic clutter layer. Since the clutter layer can serve as a generic skin or blanket of morphological information layered over the terrain model, and can contain user defined propagation characteristics per clutter class/code, this layer was perfect to reuse as a conductivity map layer.
The units of each region of conductivity are in milli-Siemens/meter (mS/m) and can be configured as labels of each clutter class/code to give the map distinction in the HTZ interface.
In order to properly model the radio wave propagation of MF signals, ATDI has also integrated the latest ITU recommendations specific to MF Groundwave propagation: ITU-R P.368-9 and ITU-R M.1467-1.
calculation feature used to generate the field strength received predictions for each pixel on the map is based on the integration of ITU-R P.368-9 into HTZ’s propagation engine.
The ITU-R P.368-9 model depends on the input of conductivity and permittivity data which is provided by the ITU maps described previously.
These values provide the ITU-R P.368 Groundwave model with the appropriate attenuation information to model MF propagation over land and sea allowing HTZ to generate MF Groundwave coverage plots.
In order to make sure that the receive sensitivity of each radio network element is configured appropriately, with respect to their immediate environmental conditions and time of year,
HTZ has also integrated a NOISDAT calculator derived from ITU-R M.1467-1.


The NOISEDAT Calculator takes into consideration the operating frequency, bandwidth, signal-to-noise ratio, 90% fade margin and estimated radiated power as well as specifications of the receiver environment and season to model the variability in Noise contribution to radio propagation in the MF band.
Essentially, the NOISEDAT calculator serves as a reference to model the expected Noise Rise and respective threshold degradation at a given site of interest.
ATDI has even integrated consideration for A2 sea region in order to generate an output based on ITU-R M.1467-1 NOISEDAT calculation to give the predicted receive sensitivity in dBm and dB-V/m as well as range in nautical miles and kilometers. This information is used to calibrate HTZ’s propagation engine appropriately for ship to shore (reverse coverage) calculations.


Reporting options specific to modeling Maritime Networks
ATDI tools also includes reporting features specific to modeling Maritime Communications including the ability to generate nautical mile boundaries from the coastline or from the locations of the shore stations:

ATDI continues to refine its modeling processes for MF Groundwave propagation studies in response to emerging requirements from the spectrum authorities of Coast Guards and Naval agencies all over the world.
ATDI’s strong association with the ITU, and expertise in integrating ITU recommendations into its product line allow ATDI to be the world leader in translating complex propagation phenomenon to simple, intuitive graphics that can be understood by the various policy makers and stake holders involved utilizing and managing a country’s spectral resources.
In upcoming parts of this series on modeling Maritime Communications, we will focus on newly developed features for generating probability of coverage per season and frequency for HF Skywave propagation as well as modeling HF antennas and ultimately VHF coverage and traffic analysis for Maritime Communications.