6533b82dfe1ef96bd1290a62
RESEARCH PRODUCT
A Random Trajectory Approach for the Development of Nonstationary Channel Models Capturing Different Scales of Fading
Alireza BorhaniGordon L. StuberMatthias Patzoldsubject
Computer Networks and CommunicationsComputer scienceAerospace Engineering020302 automobile design & engineering020206 networking & telecommunications02 engineering and technologysymbols.namesakeFading distribution0203 mechanical engineeringChannel state informationAutomotive Engineering0202 electrical engineering electronic engineering information engineeringElectronic engineeringTrajectorysymbolsPath lossFadingStatistical physicsElectrical and Electronic EngineeringPower delay profileGaussian processRandomnessComputer Science::Information Theorydescription
This paper introduces a new approach to developing stochastic nonstationary channel models, the randomness of which originates from a random trajectory of the mobile station (MS) rather than from the scattering area. The new approach is employed by utilizing a random trajectory model based on the primitives of Brownian fields (BFs), whereas the position of scatterers can be generated from an arbitrarily 2-D distribution function. The employed trajectory model generates random paths along which the MS travels from a given starting point to a fixed predefined destination point. To capture the path loss, the gain of each multipath component is modeled by a negative power law applied to the traveling distance of the corresponding plane wave, whereas the randomness of the path traveled results in large-scale fading. It is shown that the local received power is well approximated by a Gaussian process in logarithmic scale, even for a very limited number of scatterers. It is also shown that the envelope of the complex channel gain follows closely a Suzuki process, indicating that the proposed channel model superimposes small-scale fading and large-scale fading. The local power delay profile (PDP) and the local Doppler power spectral density (PSD) of the channel model are also derived and analyzed. nivå2
year | journal | country | edition | language |
---|---|---|---|---|
2017-01-01 |