Overview of Methods to Predict Radio & Radar Coverage and Interference using WinProp & WRAP - Part 1
Altair EmployeeSimulating Radio & Radar Coverage and Evaluating Interference
The future information society will rely on mobile communications using latest 5G, 6G and WiFi technologies to provide a wide variety of applications for which significantly higher mobile data throughputs shall be supported. Key for development and for deployment of the evolving radio access networks is to provide realistic and high-quality wave propagation models. Here various scenarios are of interest which range from indoor office over dense urban areas to new applications for the device-to-device communication as e.g. in the vehicular domain to avoid accidents and improve traffic efficiency.
- Computation-effective: High resolution map data covers nowadays larger scenarios and provides further details like trees, lamp posts, traffic signs, etc. Efficient propagation models supporting multi-threading and MPI techniques to exploit multiple nodes are therefore mandatory.
- Accuracy: The trust of the user to get realistic results when using the radio coverage simulations is key. This has been evaluated and confirmed based on comparison against many measurement campaigns in different environments. One example is given under case 3 in this article.
Altair Feko, including WinProp technology, provides a comprehensive solution and workflow to properly address the radio coverage and radio channel prediction in a wide range of environments (rural, urban, tunnel, vehicular, …). WinProp’s highly accurate and very fast propagation models support arbitrary transmitters including cellular and broadcasting sites, satellites, repeaters, and leaky feeder cables. For the network planning all relevant air interfaces are supported, including 5G, LTE, WiFi, GPS.
For radio & radar coverage planning over larger regions up to country-wide level and beyond WRAP is recommended, see case 7. Further applications cover the technical and administrative tasks related to spectrum management, interference analysis (see case 8), and network monitoring. WRAP is used at spectrum regulatory agencies (defense and civilian), armed forces and defense agencies, air traffic control agencies, telecommunication service providers incl. public safety networks, railway operators etc.
Import Maps of the Scenario
In advance the environment of interest can be set-up by converting map data from various formats, e.g. by downloading from openstreetmap.org including the building vectors and vegetation (see the video tutorial How to Convert Open Steet Map file in WinProp under youtube.com), or by downloading and converting topographical maps e.g. from USGS or other sources (have a look at the corresponding part of the WinProp intermediate level training).
We are now showing below several cases as examples.
Case 1: 5G Radio Coverage in Urban Scenarios for mmWave Bands
In 5G ultra-dense networks with a large number of base stations in urban areas shall be utilized to provide the required high data rate volumes. For this purpose multi-threading and MPI features are implemented in WinProp to compute the ray-tracing simulation for a large number of base stations simultaneously. Higher frequencies in the millimeter wave range have the most promising prospects for providing the required additional spectrum. For the application of the sophisticated WinProp wave propagation models towards 5G both the ray tracing and dominant path models have been extended to account for the specificities of the higher frequency bands. This includes the definition of the electrical properties of typical construction materials for higher frequencies up to 300 GHz, the consideration of scattering on rough surfaces via the BRDF which is the Bidirectional Reflectance Distribution Function as well as the consideration of atmospheric absorption effects like the oxygen absorption at 60 GHz.
WinProp ray tracing models have been used to estimate the elevation spread of departure angles for the efficient MIMO usage in various city environments (e.g. Copenhagen) and compare it with the 3GPP channel model [1]. In order to characterize the mmWave channel in urban areas, a wideband propagation measurement campaign at 73 GHz in New York City is presented in [2]. For the same environment a ray tracing study with WinProp has been conducted, predicting measured statistics such as path loss and angles of arrival. This allows to generalize the measurements for the channel model development, by using the ray tracing model implemented in WinProp to fill the gaps of the measurements. The comparisons between the measured and predicted results show good accuracy, verifying that the WinProp ray tracing model is able to correctly predict the propagation characteristics also at mmWave bands [2].
[1] B. Mondal, T. Thomas, H. C. Nguyen, E. Visotsky, F. Vook: “Ray Tracing Results for Elevation Angle Spread of Departure and its Impact on System Performance”, IEEE 25th Annual International Symposium on Personal, Indoor, and Mobile Radio Communications (PIMRC 2014), Washington D.C., USA, Sep. 2014.
[2] H. C. Nguyen, G. R. MacCartney Jr., T. Thomasz, T. S. Rappaport, Be. Vejlgaardz, P. Mogensen: “Evaluation of Empirical Ray-Tracing Model for an Urban Outdoor Scenario at 73 GHz E-Band”, IEEE 80th Vehicular Technology Conference (VTC Fall 2014), Vancouver, BC, Canada, Sep. 2014.
Case 2: 5G Beam-Forming and Beam-Steering
The millimeter-wave (mmWave) spectrum has opened new opportunities for 5G technology. Technologies like Massive MIMO assist in addressing some of these challenges, however, it introduces additional complexities, increasing the need for effective and accurate simulation tools that can clarify the interaction between the environment and these technologies. Massive MIMO antenna arrays transmit directed signals to specific users simultaneously within the same time/frequency band. The antenna gain provided by the beamforming partially mitigates the impact of the high pathloss in the mmWave frequency range of the 5G New Radio (NR).
A gNB transmits beams in all directions during the initial access phase, allowing the UE to select the optimal beam—a process known as beam-sweeping. Each Synchronization Signal Block (SSB) corresponds to a specific beam formed in a different direction. The control beams are active even though they sweep periodically from the predefined set of beams. WinProp allows to simulate the 5G beam-switching which improves the signal-to-noise-and-interference (SNIR) situation by enabling only the data beams that are serving active users in the simulation process. As the user moves, they may switch to another predefined beam. The serving beam is not necessarily oriented in the direct direction (gNB to UE); for instance, it could be a reflection off a building directed towards the UE.
A further evolution is beam-steering which dynamically directs radio signals towards specific users, improving signal strength and quality. Beam-steering is based on phased array antennas, where the signal phases fed to the antenna elements are adjusted to form a focused beam in the desired direction to follow the moving user. An example of how the data beam from the antenna array is serving a user moving along a trajectory at different times is shown in the next picture:
Case 3: Validation of Prediction Accuracy in 5G Test Bed – Simulations vs Measurements
Virtual-Drive Tests are often used in automotive to accelerate the development of the vehicular antennas. Altair partners successfully used our solution for evaluating the V2X connectivity in the Rosenheim test network. Simulations were conducted at different frequency bands including band 28 at 763 MHz and band 7 at 2685 MHz to evaluate different antenna configurations and test the MIMO performance. The comparison of the simulated (red) and measured (green) RSRP signal levels for 5G test sites along the 6 km long test track in Rosenheim city center shows good agreement as can be seen in the picture below.
