Mobility-dependent small-scale propagation model for applied simulation studies
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Mobility-dependent small-scale propagation model for applied simulation studies Dmitri Moltchanov
Abstract We propose an extension to existing wireless channel modeling techniques introducing a notion of mobility behavior of the user. We represent large-scale propagation characteristics of wireless channels as a mobilitydependent stochastic process that explicitly tracks the movement of the user between areas with different received local average signal strength (RLASS). Our model consists of two different parts: mobility model and propagation model. Mobility of the user is modeled by a Markov chain with finite state space. Large-scale propagation characteristics of wireless channel are represented as a function of mobility model. Small-scale propagation characteristics are then obtained taking into account shadowing of the line-of-sight propagation path. Based on the amount of available information regarding a given landscape environment we develop two different parametrization methods (i) RLASS values are available for limited number of points in a given landscape and (ii) RLASS information is not available. The model is suitable for simulation studies of applications’ performance in presence of RLASS changes caused by movement of the user. 1 Introduction To estimate performance of wireless channels propagation models are often used. We distinguish between large-scale and small-scale models. The former models capture propagation characteristics on a coarse granularity using the notion of the received local average signal strength (RLASS), see e.g., [1-3]. Models characterizing rapid changes of the received signal strength are called small-scale propagation models, see e.g., [4-6]. These models capture propagation characteristics on a finer granularity. Neither large-scale nor small-scale models take into account the signal strength attenuation caused by movements of a user. To be precise small-scale propagation models do take into account the so-called small-scale mobility of the user over short distances [7]. Such models describe rapid fluctuations around a constant mean which are called fading. Such processes are implicitly assumed to be stationary at least in the second-order sense and mean equals to the received local average signal strength (RLASS). However, if we would consider larger travel distances (i.e., more than just few meters) RLASS starts to vary and the most important factors Correspondence: [email protected] Department of Communication Engineering, Tampere University of Technology, P.O. Box 553, Tampere, Finland
affecting it are terrain, speed of a mobile and distance from between transmitter and the receiver. In this article, contrarily to most small-scale propagation models proposed so far, we explicitly take into account two of these three factors–terrain and mobility of a user over it. In a mobile environment a user is allowed to change its position at any instant of time and these movements are not restricted to short travel distances. A receiver during a single ses
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