AZB Rectangle Shrinkage Method and Heterogeneous Computing Accelerated Full Image Theory Method Ray Tracing Enabling Complex and Massive Outdoor 6G Propagation Modeling

Until now, despite their high accuracy, the utilization of the conventional image theory method ray tracers was limited to simple simulation environments with small number of field observation points and low maximum ray bouncing order due to their poor computational efficiency. This study presents a novel full-3D AZB rectangle shrinkage method and heterogeneous computing accelerated image theory method ray tracing framework for complex and massive outdoor propagation modeling. The proposed framework is divided into three parts: 1. Visibility preprocessing part. 2. Visibility tree generation part: in this part, a novel AZB rectangle shrinkage method that accelerates and reduces generation speed and size of visibility tree is proposed. 3. Shadow testing and field calculation part: in this part, a heterogeneous computing algorithm that can make possible to handle a large amount of field observation points is proposed. It is demonstrated that the proposed framework is faster more than 651 times than the image theory method solver of WinProp. Also, it is confirmed that the proposed ray tracing framework can handle 1km x 1km wide and dense urban outdoor simulation with up to the maximum ray bouncing order of 6 and thousands of field observation points. The proposed ray tracing framework would be a cornerstone of future image theory method ray tracing techniques for complex and massive scenarios that was exclusive to the shooting and bouncing rays method ray tracers

Tools for ray tracing based radio channel modeling and simulation

Abstract. Ray tracing-based methods have become the state of the art for radio channel propagation modeling simulations. They provide a way to deterministically simulate field strength and multidispersive characteristics of the radio channel, and thus, offer a faster and easier alternative to measuring. Ray tracing is also an important tool for validating algorithms, and many applications can utilize the simulation results. As the wireless networks suffer from increasing complexity, the interest in machine learning and artificial intelligence solutions is increasing as well, and in this context the simulation results can be utilized as training data. We introduce the relevant theory in radio propagation modeling in the context of ray tracing, followed by theory of graphics processing unit-based computing, architecture, and ray tracing. We present multiple existing graphics processing unit and ray tracing-based radio channel propagation modeling implementations from the literature. We then develop multiple optimized versions of an existing environment discretization-based path search implementation and develop a path refiner for refining the coarse paths generated by the path search. The path refiner computes the optimal paths, and then validates them by utilizing ray tracing. Experiments for the developed solutions are conducted with an indoor and an outdoor model on two different computer setups. We achieve on average over 25 times faster computation in the outdoor scene and over 4 times faster computation in the indoor scene when compared to the original path search implementation. The path refiner is able to find the optimal paths fulfilling the Fermat’s principle of least time on average for over 96% of the coarse paths in the outdoor scene, and for over 99% in the indoor scene. From these refined paths, on average about 62% pass the validation phase in the outdoor case, and around 30% in the indoor case. The results show that the path refinement combined with validation is essential for improving the quality of the paths found by the initial discretization-based search.Työkaluja säteenseurantaan perustuvaan radiokanavamallinnukseen ja simulointiin. Tiivistelmä. Säteenseurantaan perustuvat menetelmät ovat edistyneintä tekniikkaa radiokanavien etenemisen mallinnussimulaatioissa. Ne tarjoavat tavan deterministisesti arvioida radiokanavan kentänvoimakkuutta ja monidispersiivisiä ominaisuuksia ja siten tarjoavat nopeamman ja helpomman vaihtoehdon mittaamiselle. Säteenseuranta on myös tärkeä työkalu algoritmien validoinnissa ja useissa sovelluksissa voidaan hyödyntää simulointien tuloksia. Langattomien verkkojen monimutkaisuuden lisääntyessä myös kiinnostus koneoppimis- ja tekoälypohjaisiin ratkaisuihin lisääntyy, ja tässä yhteydessä simulointien tuloksia voidaan hyödyntää opetusdatana. Tässä työssä esitellään teoriaa radiokanavan etenemisen mallinnuksesta säteenseurantaan perustuen, jonka jälkeen esitellään näytönohjainpohjaisen laskennan, arkkitehtuurin, sekä säteenseurannan teoriaa. Tämän jälkeen tarkastellaan useita olemassa olevia näytönohjain- ja säteenseurantapohjaisia radiokanavan etenemistä mallintavia toteutuksia. Työssä kehitetään useita optimoituja versioita olemassa olevasta ympäristön diskretisointiin perustuvasta polunetsintätoteutuksesta ja kehitetään poluntarkentaja tarkentamaan sen tuottamia epäoptimaalisia polkuja. Poluntarkentaja laskee optimaaliset polut ja validoi ne hyödyntämällä säteenseurantaa. Ratkaisuiden tehokkuutta arvioidaan sekä ulko- että sisätilan malleille tehtävillä laskennoilla kahdella eri tietokoneella. Paras polunetsintäversio saavuttaa keskimäärin yli 25 kertaa nopeamman laskennan ulkotilassa ja yli 4 kertaa nopeamman laskennan sisätilassa verrattaessa alkuperäiseen toteutukseen. Poluntarkentaja löytää optimaaliset polut, jotka täydentävät Fermat’n periaatteen lyhyimmästä ajasta keskimäärin yli 96 prosentille karkeista poluista ulkotilassa ja yli 99 prosentille sisätilassa. Näistä tarkennetuista poluista keskimäärin noin 62 prosenttia pääsee läpi validoinnista ulkotilassa ja noin 30 prosenttia sisätilassa. Tulokset osoittavat, että polkujen tarkennus ja validointi ovat tärkeitä alkuperäisen diskretisointipohjaisen haun löytämien polkujen laadun parantamiseksi

Applying the finite-difference time-domain to the modelling of large-scale radio channels

A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Doctor of Philosophy (PhD)Finite-difference models have been used for nearly 40 years to solve electromagnetic problems of heterogeneous nature. Further, these techniques are well known for being computationally expensive, as well as subject to various numerical artifacts. However, little is yet understood about the errors arising in the simulation of wideband sources with the finitedifference time-domain (FDTD) method. Within this context, the focus of this thesis is on two different problems. On the one hand, the speed and accuracy of current FDTD implementations is analysed and increased. On the other hand, the distortion of numerical pulses is characterised and mitigation techniques proposed. In addition, recent developments in general-purpose computing on graphics processing units (GPGPU) have unveiled new methods for the efficient implementation of FDTD algorithms. Therefore, this thesis proposes specific GPU-based guidelines for the implementation of the standard FDTD. Then, metaheuristics are used for the calibration of a FDTD-based narrowband simulator. Regarding the simulation of wideband sources, this thesis uses first Lagrange multipliers to characterise the extrema of the numerical group velocity. Then, the spread of numerical Gaussian pulses is characterised analytically in terms of the FDTD grid parameters. The usefulness of the proposed solutions to the previously described problems is illustrated in this thesis using coverage and wideband predictions in large-scale scenarios. In particular, the indoor-to-outdoor radio channel in residential areas is studied. Furthermore, coverage and wideband measurements have also been used to validate the predictions. As a result of all the above, this thesis introduces first an efficient and accurate FDTD simulator. Then, it characterises analytically the propagation of numerical pulses. Finally, the narrowband and wideband indoorto-outdoor channels are modeled using the developed techniques

WiSegRT: Dataset for Site-Specific Indoor Radio Propagation Modeling with 3D Segmentation and Differentiable Ray-Tracing

The accurate modeling of indoor radio propagation is crucial for localization, monitoring, and device coordination, yet remains a formidable challenge, due to the complex nature of indoor environments where radio can propagate along hundreds of paths. These paths are resulted from the room layout, furniture, appliances and even small objects like a glass cup. They are also influenced by the object material and surface roughness. Advanced machine learning (ML) techniques have the potential to take such non-linear and hard-to-model factors into consideration. However, extensive and fine-grained datasets are urgently required. This paper presents WiSegRT, an open-source dataset for indoor radio propagation modeling. Generated by a differentiable ray tracer within the segmented 3-dimensional (3D) indoor environments, WiSegRT provides site-specific channel impulse responses for each grid point relative to the given transmitter location. We expect WiSegRT to support a wide-range of applications, such as ML-based channel prediction, accurate indoor localization, radio-based object detection, wireless digital twin, and more.Comment: accepted by IEEE ICNC 202

Proceedings Virtual Imaging Trials in Medicine 2024

This submission comprises the proceedings of the 1st Virtual Imaging Trials in Medicine conference, organized by Duke University on April 22-24, 2024. The listed authors serve as the program directors for this conference. The VITM conference is a pioneering summit uniting experts from academia, industry and government in the fields of medical imaging and therapy to explore the transformative potential of in silico virtual trials and digital twins in revolutionizing healthcare. The proceedings are categorized by the respective days of the conference: Monday presentations, Tuesday presentations, Wednesday presentations, followed by the abstracts for the posters presented on Monday and Tuesday

Virtual clinical trials in medical imaging: a review

The accelerating complexity and variety of medical imaging devices and methods have outpaced the ability to evaluate and optimize their design and clinical use. This is a significant and increasing challenge for both scientific investigations and clinical applications. Evaluations would ideally be done using clinical imaging trials. These experiments, however, are often not practical due to ethical limitations, expense, time requirements, or lack of ground truth. Virtual clinical trials (VCTs) (also known as in silico imaging trials or virtual imaging trials) offer an alternative means to efficiently evaluate medical imaging technologies virtually. They do so by simulating the patients, imaging systems, and interpreters. The field of VCTs has been constantly advanced over the past decades in multiple areas. We summarize the major developments and current status of the field of VCTs in medical imaging. We review the core components of a VCT: computational phantoms, simulators of different imaging modalities, and interpretation models. We also highlight some of the applications of VCTs across various imaging modalities

Evaluation of mmWave 5G Performance by Advanced Ray Tracing Techniques

Technological progress leads to the emergence of new concepts, which can change people’s everyday lives and accelerate the transformation of many industries. Among the more recent of these revolutionary concepts are big data analysis, artificial intelligence, augmented/virtual reality, quantum computing, and autonomous vehicles. However, this list would be incomplete without referring to fifth-generation (5G) technology, which is driven by several trends. First, the exponential growth of the worldwide monthly smartphone traffic up to 50 petabytes during the next three years will require the development of mobile networks supporting high datasharing capabilities, excellent spectral efficiency, and gigabits per second of throughput. Another trend is Industry 4.0/5.0 (also called the smart factory), which refers to advanced levels of automation requiring millions of distributed sensors/devices connected into a scalable and smart network. Finally, the automation of critical industrial processes, as well as communication between autonomous vehicles, will require 99.999% reliability and under 1 ms latency as they also become the drivers for the emergence of 5G. Besides traditional sub-6 GHz microwave spectrum, the 5G communication encompasses the novel millimeter-wave bands to mitigate spectrum scarcity and provide large bandwidth of up to several GHz. However, there are challenges to be overcome with the millimeter-wave band. The band suffers from higher pathloss, more atmospheric attenuation, and higher diffraction losses than microwave signals. Because the millimeter-wave band has such a small wavelength (< 1 cm), it is now feasible to implement compact antenna arrays. This enables the use of beamforming and multi-input and multi-output techniques. In this thesis, advanced ray tracing methodology is developed and utilized to simulate the propagation mechanisms and their effect on the system-level metrics. The main novelty of this work is in the introduction of typical millimeter-wave 5G technologies into channel modelling and propagation specifics into the system-level simulation, as well as the adaptation of the ray tracing methods to support extensive simulations with multiple antennas

Terahertz Wireless Channels: A Holistic Survey on Measurement, Modeling, and Analysis

Terahertz (0.1-10 THz) communications are envisioned as a key technology for sixth generation (6G) wireless systems. The study of underlying THz wireless propagation channels provides the foundations for the development of reliable THz communication systems and their applications. This article provides a comprehensive overview of the study of THz wireless channels. First, the three most popular THz channel measurement methodologies, namely, frequency-domain channel measurement based on a vector network analyzer (VNA), time-domain channel measurement based on sliding correlation, and time-domain channel measurement based on THz pulses from time-domain spectroscopy (THz-TDS), are introduced and compared. Current channel measurement systems and measurement campaigns are reviewed. Then, existing channel modeling methodologies are categorized into deterministic, stochastic, and hybrid approaches. State-of-the-art THz channel models are analyzed, and the channel simulators that are based on them are introduced. Next, an in-depth review of channel characteristics in the THz band is presented. Finally, open problems and future research directions for research studies on THz wireless channels for 6G are elaborated.Comment: to appear in IEEE Communications Surveys and Tutorial