5G 3GPP-like Channel Models for Outdoor Urban Microcellular and Macrocellular Environments

For the development of new 5G systems to operate in bands up to 100 GHz, there is a need for accurate radio propagation models at these bands that currently are not addressed by existing channel models developed for bands below 6 GHz. This document presents a preliminary overview of 5G channel models for bands up to 100 GHz. These have been derived based on extensive measurement and ray tracing results across a multitude of frequencies from 6 GHz to 100 GHz, and this document describes an initial 3D channel model which includes: 1) typical deployment scenarios for urban microcells (UMi) and urban macrocells (UMa), and 2) a baseline model for incorporating path loss, shadow fading, line of sight probability, penetration and blockage models for the typical scenarios. Various processing methodologies such as clustering and antenna decoupling algorithms are also presented.Comment: To be published in 2016 IEEE 83rd Vehicular Technology Conference Spring (VTC 2016-Spring), Nanjing, China, May 201

An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

Analysis of Energy Consumption Performance towards Optimal Radioplanning of Wireless Sensor Networks in Heterogeneous Indoor Environments

In this paper the impact of complex indoor environment in the deployment and energy consumption of a wireless sensor network infrastructure is analyzed. The variable nature of the radio channel is analyzed by means of deterministic in-house 3D ray launching simulation of an indoor scenario, in which wireless sensors, based on an in-house CyFi implementation, typically used for environmental monitoring, are located. Received signal power and current consumption measurement results of the in-house designed wireless motes have been obtained, stating that adequate consideration of the network topology and morphology lead to optimal performance and power consumption reduction. The use of radioplanning techniques therefore aid in the deployment of more energy efficient elements, optimizing the overall performance of the variety of deployed wireless systems within the indoor scenario

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

mTOSSIM: A simulator that estimates battery lifetime in wireless sensor networks

Knowledge of the battery lifetime of the wireless sensor network is important for many situations, such as in evaluation of the location of nodes or the estimation of the connectivity, along time, between devices. However, experimental evaluation is a very time-consuming task. It depends on many factors, such as the use of the radio transceiver or the distance between nodes. Simulations reduce considerably this time. They allow the evaluation of the network behavior before its deployment. This article presents a simulation tool which helps developers to obtain information about battery state. This simulator extends the well-known TOSSIM simulator. Therefore it is possible to evaluate TinyOS applications using an accurate model of the battery consumption and its relation to the radio power transmission. Although an specific indoor scenario is used in testing of simulation, the simulator is not limited to this environment. It is possible to work in outdoor scenarios too. Experimental results validate the proposed model.Junta de Andalucía P07-TIC-02476Junta de Andalucía TIC-570