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Alireza Borhani disputerer for ph.d-graden tirsdag 25. november med avhandlingen “Modelling and Analysis of Non-stationary Mobile Fading Channels Using Brownian Random Trajectory Models”.
Artikkelen er mer enn ett år gammel, og kan inneholde utdatert informasjon.
Alireza Borhani har fulgt doktorgradsprogrammet ved Fakultet for teknologi og realfag med spesialisering i IKT, der han har arbeidet i «Mobile Communications Group», ledet av professor Matthias Pätzold.
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 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.
Under the assumptions that the scatterers are fixed and the observation time is short enough, we develop the stationary channel models. We show that the proposed channel models are highly flexible and outperform several other geometric models in the sense of matching empirical data.
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.
It is shown that relatively fast moving scatterers have a major impact on both V2V and fixed-to-fixed (F2F) communication links. 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. 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.
Kandidaten: Alireza Borhani received the B.E. degree in biomedical engineering from Azad University of Tehran, Iran, in 2007 and the M.E. degree in communication engineering from Shahed University, Tehran, Iran. Since 2011, he worked toward the Ph.D. degree at the Department of Information and Communication Technology, University of Agder (UiA), Campus Grimstad.. He is currently working as an associate researcher at the UiA.
Prøveforelesning og disputas finner sted i Auditorium C2-040, Campus Grimstad
Instituttleder Andreas Prinz leder disputasen
Tid for prøveforelesning: Tirsdag 25. november 2014 kl 10:00
Oppgitt emne for prøveforelesning: “Advanced automotive radars for accurate monitoring of car environments towards increased road traffic and improved driving safety”.
Tid for disputas: Tirsdag25. november 2014 kl 12:00
Tittel på avhandling: “Modelling and Analysis of Non-stationary Mobile Fading Channels Using Brownian Random Trajectory Models”
Søk etter avhandlingen i AURA - Agder University Research Archive, som er et digitalt arkiv for vitenskapelige artikler, avhandlinger og masteroppgaver fra ansatte og studenter ved Universitetet i Agder. AURA blir jevnlig oppdatert.
Førsteopponent: Professor Alain Sibille, Telecom ParisTech
Bedømmelseskomitéen er ledet av førsteamanuensis Geir Køien, UiA