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Combined Model for Outdoor to Indoor Radio Propagation
Abstract and Figures
In this paper, a new model used to compute the outdoor to indoor signal strength emitted by a base station is presented. This model is based on the combination of 2 existing models: IRLA (Intelligent Ray Launching), a 3D geometric-like model especially optimized for outdoor predictions, and MR-FDPF (Multi Resolution Frequency Domain ParFlow), a 2D FDTD-like model initially implemented for indoor propagation. The combination of these models implies the conversion of the ray launching signals on the border of the buildings, into virtual source flows that will be used as an input for the indoor model. The performance of the new combined model is evaluated via measurements, and it appears to be an efficient solution for radio network planning, both in term of accuracy and computational cost.
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... The application of such network in indoor area like office, factory or in outdoor or in vegetated creates different environment or channel model through which the communication path is set-up between the source and destination node. The appropriate modelling of the propagation channel and its elements is required to accomplish projects capable of attending the demands of different coverage areas (Roche et al., 2010;Alejos et al., 2012;Fernández and Cuiñas, 2013). Propagation loss is an important parameter to analyse the transmission range of the network. ...
... Path loss is defined as the difference between received and transmitted power. A MIMO channel with M transmitting and N receiving antennas, the power can be described by channel matrix (Roche et al., 2010). So, the path loss can be calculated as ...
Developing applications, especially real time ones mobile ad hoc network (MANET) requires a reasonable assurance of the likely performance of the network. MANET is realised by mobile nodes which communicate difficult task. Amongst many important properties of radio propagation model has to be selected carefully. This paper presents a hybrid propagation model of ad hoc network with multiple numbers of antennas. The hybrid technique ensures improved accuracy and practicality of the entire modelling environment. Currently study a modelled network consisting of ad hoc nodes with multiple antennas in different terrain and the propagation loss is calculated of the modelled network for the each ad hoc node. A loss less routing algorithm is implemented here and finally minimum loss route is selected for propagation in different terrain. 2017 Inderscience Enterprises Ltd.
... In [20], the authors further combine the IRLA model with a FDTDlike method: MR-FDPF (Multi Resolution Frequency Domain ParFlow) [21] for an indoor to outdoor scenario where the accuracy was validated by the measurement campaign. In [22] and [23], the authors combine the IRLA model with MR-FDPF for outdoor to indoor scenarios. Based on the aforementioned work on the IRLA model [24], This article will contribute by providing: • Details on the calibration of the indoor materials. ...
This article describes the indoor IRLA (Intelli-gent Ray Launching Algorithm), which originates from an efficient outdoor propagation prediction model. Implemen-tation and validation are given in detail. An indoor office scenario is selected and simulations via the IRLA model and two other reference models have been performed. Predic-tions are analyzed and recommendations are given. Results show that the indoor IRLA model is suitable for indoor wire-less network planning and optimization process. Keywords Intelligent ray launching algorithm, radio wave propa-gation prediction, indoor scenarios, path loss models, in-building network planning.
Multiple-input multiple-output (MIMO) system is a very promising technique in modern wireless communication systems, which can meet the demand of high data rate with limited bandwidth. Integration of MIMO technology with mobile ad hoc network can improve the performance of transmission process in hazardous environment. In order to design a real MIMO wireless system and predict its performance under certain circumstances, it is necessary to have accurate MIMO wireless channel models for different scenarios. Mobile ad hoc network with multiple antennas suffers scattering effects. A combination of two ring model and random scattering model is described in this paper to evaluate channel impulse response of the network. Channel impulse response or channel matrix is used to estimate the propagation loss of the MIMO-based mobile ad hoc network in different terrain. Finally, a minimum loss secure path selection is described here using path loss-based administrator selection secure routing protocol (PASR) protocol to select loss less secure route for transmission.
This chapter is dedicated to radio channel modeling for 4G networks. In addition to recent results in the area of 4G channel modeling at large, including complex environments such as aircrafts, COST 2100 has dealt with a number of specific topics which are presented in this chapter.
Improved deterministic methods, including models of diffuse components are detailed in Sect. 3.2. The developed models namely propose new methods to account for macroscopic diffuse scattering in ray-tracing tools.
The measurement-based modeling of the same diffuse or dense multipath components has represented one major research topic in COST 2100, especially regarding the extraction of such components from experimental data (Sect. 3.3).
Another important topic of research has concerned the modeling of the polarization behavior of wireless channels (see Sect. 3.4), as multipolarized antenna arrays appear more and more as a realistic implementation of MIMO systems.
The specific representation and modeling of multilink scenarios is dealt with in Sect. 3.5. Considering the correlations between multiple links is a significant requirement to design robust schemes in cooperative, relay or multihop networks.
Finally, the COST 2100 model is presented in Sect. 3.6. Starting from a single-link implementation based on the COST 273 model (available online), it builds upon the work described in this chapter to propose an updated version of the COST 2100 model including enhancements such as diffuse and cross-polar components, as well as multi-link aspects.
Multiple-input multiple-output (MIMO) system is a very promising
technique in modern wireless communication systems, which can meet the demand of high data rate with limited bandwidth. Integration of MIMO technology with mobile ad hoc network can improve the performance of transmission process in hazardous environment. In order to design a real MIMO wireless system and predict its performance under certain circumstances, it is necessary to have accurate MIMO wireless channel models for different scenarios. Mobile ad hoc network with multiple antennas suffers
scattering effects. A combination of two ring model and random scattering model is described in this paper to evaluate channel impulse response of the network. Channel impulse response or channel matrix is used to estimate the propagation loss of the MIMO-based mobile ad hoc network in different terrain. Finally, a minimum loss secure path selection is described here using
path loss-based administrator selection secure routing protocol (PASR) protocol to select loss less secure route for transmission.
Introduction Modelling Principles Empirical Propagation Models Deterministic Models Hybrid Models Acknowledgements References
A new approach for predicting coverage of wireless LAN at 2.4 GHz is presented. Coverage prediction is one of the core parts of indoor wireless LAN planning tools. The main concern it has to deal with is providing a good trade-off between prediction accuracy and computational load. Usual approaches belong to either empirical or deterministic methods. A new perspective has recently been offered that exploits a discrete formalism based on the TLM formulation. It is referred to as Multi-Resolution Frequency Domain ParFlow (MR-FDPF). While ray-tracing handles computational load by restricting the number of considered paths, the proposed approach acts by adapting the spatial resolution. This paper presents the straight lines of MR-FDPF and details the conditions for efficient in-building coverage prediction at 2.4 GHz. In a second part this paper tackles the calibration problem and claims for an automatic calibration process to improve the fit between predictions and measurements. A couple of experiments are presented.
In this paper, we present a cluster based analysis of an outdoor-to-indoor Multiple-Input Multiple-Output (MIMO) measurement campaign, and extract model parameters for the COST273 channel model. The measurements were performed at 5.2 GHz for 159 measurement locations in an office building. Multipath component (MPC) parameters have been extracted for these positions using a high-resolution algorithm. We analyze the clustering of MPCs, i.e., grouping together of MPCs with similar DOAs, DODs, and delays. We compare cluster identification by visual inspection to automatic identification by the recently proposed algorithm of Czink et al. In the paper we include results on the intercluster properties such as the distribution of the number of clusters and the cluster powers, as well as intracluster properties such as the angle and delay spreads within the clusters. In particular, we extract parameters for the COST 273 channel model, a standardized generic model for MIMO propagation channels.
Femtocells, or home base stations, are a potential future solution for operators to increase indoor coverage and reduce network cost. In a real WiMAX femtocell deployment in residential areas covered by WiMAX macrocells, interference is very likely to occur both in the streets and certain indoor regions. Propagation models that take into account both the outdoor and indoor channel characteristics are thus necessary for the purpose of WiMAX network planning in the presence of femtocells. In this paper, the finite-difference time-domain (FDTD) method is adapted for the computation of radiowave propagation predictions at WiMAX frequencies. This model is particularly suitable for the study of hybrid indoor/outdoor scenarios and thus well adapted for the case of WiMAX femtocells in residential environments. Two optimization methods are proposed for the reduction of the FDTD simulation time: the reduction of the simulation frequency for problem simplification and a parallel graphics processing units (GPUs) implementation. The calibration of the model is then thoroughly described. First, the calibration of the absorbing boundary condition, necessary for proper coverage predictions, is presented. Then a calibration of the material parameters that minimizes the error function between simulation and real measurements is proposed. Finally, some mobile WiMAX system-level simulations that make use of the presented propagation model are presented to illustrate the applicability of the model for the study of femto- to macrointerference.
The Indoor Coverage ChallengeConcepts of FemtocellsWhy is Femtocell Important?Deployment of FemtocellsImportant Facts to Attract More CustomersThe Structure of the BookReferences
Ray-based methods such as ray tracing and ray launching have been increasingly used in radio wave propagation modelling. Ray tracing is used for point-to-point multipath prediction (for few receivers) while ray launching, being more adaptable, is more suitable for multi-point prediction. However, ray launching suffers from angular dispersion which causes rays to miss pixels when the distance from the emitter increases. Several solutions such as beam tracing or ray splitting have been proposed to resolve this, but this paper presents a new approach, which is suitable for discrete ray launching, to avoid the problem. Results show that by this approach, discrete ray launching is suitable for radio wave propagation modelling. Significant speedups are observed compared to traditional ray-based models via parallelization techniques such as multi-threading and distributed computing. Complex channel characteristics due to multipaths in the urban environment can be obtained via this method.
With the increasing need of accuracy, deterministic propagation models have been widely adopted in site-specific wireless applications. Compared to empirical models, they are usually more accurate, but time-consuming. Several acceleration techniques have reduced the simulation time and yet the computation of typical scenarios remains complex. In this paper, a novel 3D model, namely IRLA (intelligent ray launching algorithm) is presented to predict a huge number of receiver pixels (few millions) in a large scenario (few square kilometers) within few seconds, which is beneficial to relevant academics and industries.
This paper deals with channel characterization in Outdoor to Indoor (021) context. Particularly, we propose an original approach using both numerical propagation predictions and measurements of angles of arrival (AOA) and power delay profile (PDP), in order to improve the deployment techniques for WiMAX-based systems with relay cooperation.
Growing interest in providing and improving radio coverage for mobile phones and wireless LANs inside buildings has recently emerged. The need of such coverage appears mainly in office buildings, shopping malls in very complex environment. Although the three dimensional FDTD method has shown great promise, the calculation time is very environment dependent and exceeds the calculation time of ray tracing or ray launching in most cases. In this article, we focus on the theoretical estimation and comparison of FDTD and ray methods in aspects of the algorithmic complexity.
Despite their good performance, the widespread diffusion of ray tracing field-prediction models is still limited due to their high complexity and high computation time. In this paper, two different classes of methods for speeding up ray tracing urban field prediction are proposed, aimed at reducing the size of the input database and the number of rays to be handled by the algorithm. With the proposed techniques, a great computation time reduction can be achieved without sensibly affecting the accuracy of the prediction.
A full 3D hybrid method for analyzing electromagnetic wave propagation in buildings with realistic wall types and structures is presented. This hybrid method combines full-wave techniques which are used for the analysis of one unit cell of inhomogeneous periodic walls with a ray-tracing-like field calculation for the interaction between the walls. Consequently, the method can overcome the inadequacy of traditional ray-tracing in the presence of inhomogeneous periodic wall structures like cinderblock, rebar structure, etc. but is still computationally tractable. Because of this, both indoor wireless channel characterizations and signal fading statistics are shown to be more accurate with this method. Numerical results of the hybrid method are presented for two simple scenarios and validated with theory and measurement. Furthermore, numerical results for a realistic indoor scene are given and compared to a scene where the periodic walls are replaced with effective homogeneous walls. For both setups, the propagation channel is characterized, fast fading signal statistics are extracted and the inadequacies of the homogeneous wall implementation are pointed out.