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Modelling and Analysis of Non-Stationary Mobile Fading Channels Using Brownian Random Trajectory Models

Borhani, Alireza
Doctoral thesis, Peer reviewed
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URI
http://hdl.handle.net/11250/219069
Date
2014
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  • Doctoral Dissertations [269]
Abstract
The demanding mobility features of communication technologies call for the need

to advance channel models (among other needs), in which non-stationary aspects

of the channel are carefully taken into consideration. Owing to the mathematical

complexity imposed by mobility features of the mobile station (MS), the number

of non-stationary channel models proposed in the literature is very limited. The

absence of a robust trajectory model for capturing the mobility features of the MS

also adds to the depth of this gap. Not only statistically non-stationary channels, but

also physically non-stationary channels, such as vehicle-to-vehicle channels in the

presence of moving scatterers, have been rarely investigated.

In the literature, there exist two fundamental channel modelling approaches,

namely deterministic and stochastic approaches. Deterministic approaches, such as

measurement-based channel modelling, are known to be accurate, but site-specific

and economically expensive. The stochastic approaches, such as geometry-based

channel modelling, are known to be economically inexpensive, computationally

fair, but not as accurate as the deterministic approach. Among these approaches,

the geometry-based stochastic approach is the best to capture the non-stationary

aspects of the channel. In this dissertation, we employ the geometry-based stochastic approach for the

development of three types of channel models, namely stationary, physically nonstationary,

and statistically non-stationary channel models. We geometrically track

the plane waves emitted from the transmitter over the local scatterers up to the receiver,

which is assumed to be in motion. Under the assumptions that the scatterers

are fixed and the observation time is short enough, we develop the stationary channel

models. In this regard, we propose a unified disk scattering model (UDSM),

which unifies several well-established geometry-based channel models into one robust

channel model. We show that the UDSM is highly flexible and outperforms

several other geometric models in the sense of matching empirical data. In addition,

we provide a new approach to develop stationary channel models based on

delay-angle joint distribution functions.

Under the assumption that the scatterers are in motion and the observation time

is again short enough, we develop a physically non-stationary channel model. In

this connection, we model vehicle-to-vehicle (V2V) channels in the presence of

moving scatterers. Proper distributions for explaining the speed of relatively fast

and relatively slow moving scatterers are provided. The statistical properties of the

proposed channel model are also derived and validated by measured channels. It

is shown that relatively fast moving scatterers have a major impact on both V2V and fixed-to-fixed (F2F) communication links, as they are significant sources of the

Doppler spread. However, relatively slow moving scatterers can be neglected in

V2V channels, but not in F2F channels.

Under the assumption that the scatterers are fixed and the observation time is

not necessarily short anymore, we develop the statistically non-stationary channel

models. To this aim, we first introduce a new approach for generating fully spatial

random trajectories, which are supposed to capture the mobility features of the MS.

By means of this approach, we develop a highly flexible trajectory model based

on the primitives of Brownian fields (BFs). We show that the flexibility of the

proposed trajectory is threefold: 1) its numerous configurations; 2) its smoothness

control mechanism; and 3) its adaptivity to different speed scenarios. The statistical

properties of the trajectory model are also derived and validated by data collected

from empirical studies. We then introduce a new approach to develop stochastic non-stationary channel

models, the randomness of which originates from a random trajectory of the MS,

rather than from the scattering area. Based on the new approach, we develop and analyze

a non-stationary channel model using the aforementioned Brownian random

trajectory model. We show that the channel models developed by this approach are

very robust with respect to the number of scatterers, such that highly reported statistical

properties can be obtained even if the propagation area is sparsely seeded

with scatterers. We also show that the proposed non-stationary channel model superimposes

large-scale fading and small-scale fading. Moreover, we show that the

proposed model captures the path loss effect.

More traditionally, we develop and analyze two non-stationary channel models,

the randomness of which originates from the position of scatterers, but not from the

trajectory of the MS. Nevertheless, the travelling path of the MS is still determined

by a sample function of a Brownian random trajectory. It is shown that the proposed

channel models result in a twisted version of the Jakes power spectral density (PSD)

that varies in time. Accordingly, it is demonstrated that non-stationarity in time is

not in line with the common isotropic propagation assumption on the channel.
Description
Doktorgradsavhandling i informasjons- og kommunikasjonsteknologi, Universitetet i Agder, Grimstad, 2014
Publisher
Universitet i Agder / University of Agder
Series
Doctoral dissertations at University of Agder;
;95

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