INTERNATIONAL HELLENIC UNIVERSITY
`School of Science and Technology
`
`Virtual Labs #2:
`”Fading Processes-Channel Characterization”:
`Documentation
`
`Referring to Courses:
`Mobile Communication Networks,
`MSc in Information and Communication Technology Systems
`
`prepared by
`
`Liaskos Christos
`Computer Architecture and Communications Lab
`Department of Informatics
`Aristotle University of Thessaloniki
`
`Dr. Koutitas George
`School of Science and Technology
`International Hellenic University
`
`September 2010
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`Table of Contents
`
`1.0 Preface . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`2.0 Introduction: Theoretical concepts . . . . . . . . . . . . . . . . . . . . . .
`
`2.1 Fading processes
`
`. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`2.2 Rayleigh Fading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`2.3 Rician Fading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`2.4 Further reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`1
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`2
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`2
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`7
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`12
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`12
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`3.0 User’s Manual
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`. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13
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`3.1 Requirements . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`3.2
`
`Installation Notes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`3.3 Application execution and usage . . . . . . . . . . . . . . . . . . . . . . . . .
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`3.4 Simulating and obtaining results . . . . . . . . . . . . . . . . . . . . . . . . .
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`3.5 Characterizing the wireless channel
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`. . . . . . . . . . . . . . . . . . . . . . .
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`3.6 Uninstalling the application . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`13
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`13
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`14
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`22
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`22
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`23
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`4.0 Supervisor’s Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
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`4.1 Extending the application . . . . . . . . . . . . . . . . . . . . . . . . . . . .
`
`24
`
`5.0 Programmer’s Manual
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`. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25
`
`5.1 Portability . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`5.2 Explaining the directory structure . . . . . . . . . . . . . . . . . . . . . . . .
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`5.3 Conventions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`5.4 Architecture . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`5.5 List of MATLAB function files . . . . . . . . . . . . . . . . . . . . . . . . . .
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`25
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`25
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`27
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`27
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`29
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`References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
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`List of Figures
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`Figure 1 — Densely-built Manhattan has been shown to approach a Rayleigh fad-
`
`ing environment.
`
`. . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`Figure 2 — One second of Rayleigh fading with a maximum Doppler shift of 10Hz.
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`Figure 3 — One second of Rayleigh fading with a maximum Doppler shift of 100Hz.
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`Figure 4 — The autocorrelation function of the 10Hz Doppler Rayleigh fading
`
`8
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`9
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`9
`
`channel.
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`. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`10
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`Figure 5 — The normalized Doppler power spectrum of Rayleigh fading with a
`
`maximum Doppler shift of 10Hz.
`
`. . . . . . . . . . . . . . . . . . . .
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`Figure 6 — The simulation setup form.
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`. . . . . . . . . . . . . . . . . . . . . . .
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`Figure 7 — The 3D visualization form. . . . . . . . . . . . . . . . . . . . . . . . .
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`Figure 8 — Navigation Panel. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
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`Figure 9 — Navigation through mouse. . . . . . . . . . . . . . . . . . . . . . . . .
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`Figure 10 — A signal source is modulated, altered (in terms of gain) by the trans-
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`12
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`14
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`15
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`18
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`19
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`mitting antenna, endures losses according to the selected medium
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`model, suffers the effect of shadowing (only when obstructed by one of
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`the four buildings) and fading (according to selected LOS rice factor,
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`number of paths, and RMS environment). White noise is then added
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`at the entry point of the receiving antenna (selected Eb
`N0
`
`is used). The
`
`gain of the receiving antenna is taken into account (geometry and ve-
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`hicle relative position counts). The signal is then demodulated and
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`the number of erroneous bits and symbols ir measured.
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`. . . . . . . .
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`21
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`Figure 11 — Gain forms. This forms shows the antenna gains, the shadowing losses
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`and their aggregation as a function of the vehicle’s position.
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`. . . . .
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`Figure 12 — Results forms. Three distinct panels are visible or not, depending on
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`the choices of the user in the ”Simulation” panel described above. In
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`this figure, all panels are visible and active. The topmost panel shows
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`the time-variant impulse response. The user may move the ”window”
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`slider to obtain a histogram of values inside the red window. This
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`can be used for checking that the values follow the rice distribution.
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`By altering the sensitivity slider, the green line denoting the receiver’s
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`sensitivity is shifted proportionately. This affects the Average Fade
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`Duration and Level Crossing Frequency values at the lower most panel.
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`Notice that the SER/BER values correspond to a receiver of unlimited
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`sensitivity, and the extraction of their practical values is left as an
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`exercise to the user. The power delay profile is shown in the middle
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`panel. NOTICE: this form may not show if the simulation is stopped
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`prematurely, due to lack of sufficient number of results.
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`. . . . . . .
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`Figure 13 — The rayleighAWGN Simulink Model.
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`. . . . . . . . . . . . . . . . . .
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`1.0 Preface
`
`This report constitutes the documentation of the 2nd virtual laboratory environment that
`
`was developed for the ”Mobile Communication Networks” and ”Sensor Networks” courses
`
`of the MSc in Information and Communication Technology Systems, International Hellenic
`
`University.
`
`Purpose of the present work is to familiarize the user with the concepts of E/M fading pro-
`
`cesses with regard to user mobility and modulation-encoding configurations, and enable the
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`user to characterize a channel as narrowband or wideband depending on its characteristics.
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`The report consists of four main sections.
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`The fist section outlines the basics of E/M propagation theory that are examined in the
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`context of this lab. This is not intended to be a thorough study or teaching material in any
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`case, but rather a starter for more in-depth research and study.
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`The following three sections provide usage information for the simple user (student of an
`
`MSc program in Telecommunications), the supervisor (academic assistant with some knowl-
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`edge of programming in MATLAB) and the programmer (expert in generic object oriented
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`programming and particularly in MATLAB). The provided information in this leaflet intends
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`to familiarize the simple user with the graphical interface and its potential, endow the super-
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`visor with enough knowledge to create custom exercise scenarios and program expansions,
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`and provide a blueprint for the programmer that has been bestowed with the task of heavily
`
`modifying/expanding the original program.
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`Finally a list of the main MATLAB files/functions that comprise the program is supplied.
`
`Liaskos Christos, Electrical Engineer, Dpt. of Informatics, A.U.Th.
`
`September 8, 2010
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`2.0
`
`Introduction: Theoretical concepts
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`2.1 Fading processes
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`In wireless communications, fading is deviation of the attenuation that a carrier-modulated
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`telecommunication signal experiences over certain propagation media. The fading may vary
`
`with time, geographical position and/or radio frequency, and is often modelled as a random
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`process. A fading channel is a communication channel that experiences fading. In wireless
`
`systems, fading may either be due to multipath propagation, referred to as multipath in-
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`duced fading, or due to shadowing from obstacles affecting the wave propagation, sometimes
`
`referred to as shadow fading.
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`The presence of reflectors in the environment surrounding a transmitter and receiver create
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`multiple paths that a transmitted signal can traverse. As a result, the receiver sees the super-
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`position of multiple copies of the transmitted signal, each traversing a different path. Each
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`signal copy will experience differences in attenuation, delay and phase shift while travelling
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`from the source to the receiver. This can result in either constructive or destructive inter-
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`ference, amplifying or attenuating the signal power seen at the receiver. Strong destructive
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`interference is frequently referred to as a deep fade and may result in temporary failure of
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`communication due to a severe drop in the channel signal-to-noise ratio.
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`A common example of multipath fading is the experience of stopping at a traffic light and
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`hearing an FM broadcast degenerate into static, while the signal is re-acquired if the vehicle
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`moves only a fraction of a meter. The loss of the broadcast is caused by the vehicle stopping
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`at a point where the signal experienced severe destructive interference. Cellular phones can
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`also exhibit similar momentary fades.
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`Fading channel models are often used to model the effects of electromagnetic transmission of
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`information over the air in cellular networks and broadcast communication. Fading channel
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`models are also used in underwater acoustic communications to model the distortion caused
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`by the water. Mathematically, fading is usually modeled as a time-varying random change
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`in the amplitude and phase of the transmitted signal.
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`Slow versus fast fading
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`The terms slow and fast fading refer to the rate at which the magnitude and phase change
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`imposed by the channel on the signal changes. The coherence time is a measure of the
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`minimum time required for the magnitude change of the channel to become uncorrelated
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`from its previous value.
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`• Slow fading arises when the coherence time of the channel is large relative to the delay
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`constraint of the channel. In this regime, the amplitude and phase change imposed by
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`the channel can be considered roughly constant over the period of use. Slow fading can
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`be caused by events such as shadowing, where a large obstruction such as a hill or large
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`building obscures the main signal path between the transmitter and the receiver. The
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`amplitude change caused by shadowing is often modeled using a log-normal distribution
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`with a standard deviation according to the log-distance path loss model.
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`• Fast fading occurs when the coherence time of the channel is small relative to the delay
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`constraint of the channel. In this regime, the amplitude and phase change imposed by
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`the channel varies considerably over the period of use.
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`In a fast-fading channel, the transmitter may take advantage of the variations in the chan-
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`nel conditions using time diversity to help increase robustness of the communication to a
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`temporary deep fade. Although a deep fade may temporarily erase some of the information
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`transmitted, use of an error-correcting code coupled with successfully transmitted bits dur-
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`ing other time instances (interleaving) can allow for the erased bits to be recovered. In a
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`slow-fading channel, it is not possible to use time diversity because the transmitter sees only
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`a single realization of the channel within its delay constraint. A deep fade therefore lasts
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`the entire duration of transmission and cannot be mitigated using coding.
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`The coherence time of the channel is related to a quantity known as the Doppler spread of the
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`channel. When a user (or reflectors in its environment) is moving, the user’s velocity causes
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`a shift in the frequency of the signal transmitted along each signal path. This phenomenon is
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`known as the Doppler shift. Signals traveling along different paths can have different Doppler
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`shifts, corresponding to different rates of change in phase. The difference in Doppler shifts
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`between different signal components contributing to a single fading channel tap is known as
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`the Doppler spread. Channels with a large Doppler spread have signal components that are
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`each changing independently in phase over time. Since fading depends on whether signal
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`components add constructively or destructively, such channels have a very short coherence
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`time. In general, coherence time is inversely related to Doppler spread, typically expressed
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`as
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`k D
`
`s
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`Tc =
`
`where Tc is the coherence time, Ds is the Doppler spread, and k is a constant taking on
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`values in the range of 0.25 to 0.5.
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`Flat versus frequency-selective fading
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`As the carrier frequency of a signal is varied, the magnitude of the change in amplitude will
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`vary. The coherence bandwidth measures the separation in frequency after which two signals
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`will experience uncorrelated fading. In flat fading, the coherence bandwidth of the channel
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`is larger than the bandwidth of the signal. Therefore, all frequency components of the signal
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`will experience the same magnitude of fading. In frequency-selective fading, the coherence
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`bandwidth of the channel is smaller than the bandwidth of the signal. Different frequency
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`components of the signal therefore experience decorrelated fading. Since different frequency
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`components of the signal are affected independently, it is highly unlikely that all parts of the
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`signal will be simultaneously affected by a deep fade. Certain modulation schemes such as
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`OFDM and CDMA are well-suited to employing frequency diversity to provide robustness
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`to fading. OFDM divides the wideband signal into many slowly modulated narrowband
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`subcarriers, each exposed to flat fading rather than frequency selective fading. This can
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`be combated by means of error coding, simple equalization or adaptive bit loading. Inter-
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`symbol interference is avoided by introducing a guard interval between the symbols. CDMA
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`uses the Rake receiver to deal with each echo separately. Frequency-selective fading channels
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`are also dispersive, in that the signal energy associated with each symbol is spread out in
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`time. This causes transmitted symbols that are adjacent in time to interfere with each
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`other. Equalizers are often deployed in such channels to compensate for the effects of the
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`intersymbol interference. The echoes may also be exposed to Doppler shift, resulting in a
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`time varying channel model.
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`Fading models
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`Examples of popular fading models for the distribution of the attenuation are:
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`• Rayleigh fading
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`• Rician fading
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`Less popular models not examined in this context are:
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`• Nakagami fading
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`• Weibull fading
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`• Dispersive fading models, with several echoes, each exposed to different delay, gain and
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`phase shift, often constant. This results in frequency selective fading and inter-symbol
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`interference. The gains may be Rayleigh or Rician distributed. The echoes may also
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`be exposed to Doppler shift, resulting in a time varying channel model.
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`• Log-normal shadow fading
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`Mitigation
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`Fading can cause poor performance in a communication system because it can result in a
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`loss of signal power without reducing the power of the noise. This signal loss can be over
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`some or all of the signal bandwidth. Fading can also be a problem as it changes over time:
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`communication systems are often designed to adapt to such impairments, but the fading can
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`change faster than the adaptations can be made. In such cases, the probability of experi-
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`encing a fade (and associated bit errors as the signal-to-noise ratio drops) on the channel
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`becomes the limiting factor in the link’s performance. The effects of fading can be combated
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`by using diversity to transmit the signal over multiple channels that experience independent
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`fading and coherently combining them at the receiver. The probability of experiencing a
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`fade in this composite channel is then proportional to the probability that all the component
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`channels simultaneously experience a fade, a much more unlikely event.
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`Diversity can be achieved in time, frequency, or space. Common techniques used to overcome
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`signal fading include:
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`• Diversity reception and transmission
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`• OFDM
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`• Rake receivers
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`• Spacetime codes
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`• MIMO
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`2.2 Rayleigh Fading
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`As described, Rayleigh fading is a statistical model for the effect of a propagation environ-
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`ment on a radio signal, such as that used by wireless devices.
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`Rayleigh fading models assume that the magnitude of a signal that has passed through such
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`a transmission medium (also called a communications channel) will vary randomly, or fade,
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`according to a Rayleigh distribution the radial component of the sum of two uncorrelated
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`Gaussian random variables.
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`Rayleigh fading is viewed as a reasonable model for tropospheric and ionospheric signal
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`propagation as well as the effect of heavily built-up urban environments on radio signals.
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`Rayleigh fading is most applicable when there is no dominant propagation along a line of
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`sight between the transmitter and receiver. If there is a dominant line of sight, Rician fading
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`may be more applicable.
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`The model
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`Rayleigh fading is a reasonable model when there are many objects in the environment that
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`scatter the radio signal before it arrives at the receiver. The central limit theorem holds
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`that, if there is sufficiently much scatter, the channel impulse response will be well-modeled
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`as a Gaussian process irrespective of the distribution of the individual components. If there
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`is no dominant component to the scatter, then such a process will have zero mean and phase
`evenly distributed between 0 and 2 · π radians. The envelope of the channel response will
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`therefore be Rayleigh distributed.
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`Often, the gain and phase elements of a channel’s distortion are conveniently represented as
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`a complex number. In this case, Rayleigh fading is exhibited by the assumption that the real
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`and imaginary parts of the response are modeled by independent and identically distributed
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`zero-mean Gaussian processes so that the amplitude of the response is the sum of two such
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`processes.
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`Applicability
`
`The requirement that there be many scatterers present means that Rayleigh fading can be
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`a useful model in heavily built-up city centres where there is no line of sight between the
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`transmitter and receiver and many buildings and other objects attenuate, reflect, refract and
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`diffract the signal. Experimental work in Manhattan has found near-Rayleigh fading there.
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`In tropospheric and ionospheric signal propagation the many particles in the atmospheric
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`layers act as scatterers and this kind of environment may also approximate Rayleigh fading.
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`If the environment is such that, in addition to the scattering, there is a strongly dominant
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`signal seen at the receiver, usually caused by a line of sight, then the mean of the random
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`process will no longer be zero, varying instead around the power-level of the dominant path.
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`Such a situation may be better modelled as Rician fading.
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`Figure 1: Densely-built Manhattan has been shown to approach a Rayleigh fading environ-
`ment.
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`Note that Rayleigh fading is a small-scale effect. There will be bulk properties of the en-
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`vironment such as path loss and shadowing upon which the fading is superimposed. How
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`rapidly the channel fades will be affected by how fast the receiver and/or transmitter are
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`moving. Motion causes Doppler shift in the received signal components. The figures show
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`the power variation over 1 second of a constant signal after passing through a single-path
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`Rayleigh fading channel with a maximum Doppler shift of 10 Hz and 100 Hz. These Doppler
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`shifts correspond to velocities of about 6 km/h (4 mph) and 60 km/h (40 mph) respectively
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`at 1800 MHz, one of the operating frequencies for GSM mobile phones. This is the classic
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`shape of Rayleigh fading. Note in particular the ’deep fades’ where signal strength can drop
`by a factor of several thousand, or 30 − 40 dB.
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`Figure 2: One second of Rayleigh fading with a maximum Doppler shift of 10Hz.
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`Figure 3: One second of Rayleigh fading with a maximum Doppler shift of 100Hz.
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`Properties
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`Since it is based on a well-studied distribution with special properties, the Rayleigh distri-
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`bution lends itself to analysis, and the key features that affect the performance of a wireless
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`network have analytic expressions. Note that the parameters discussed here are for a non-
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`static channel. If a channel is not changing with time, clearly it does not fade and instead
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`remains at some particular level. Separate instances of the channel in this case will be un-
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`correlated with one another owing to the assumption that each of the scattered components
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`fades independently. Once relative motion is introduced between any of the transmitter,
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`receiver and scatterers, the fading becomes correlated and varying in time.
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`Correlation
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`The normalized autocorrelation function of a Rayleigh faded channel with motion at a con-
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`stant velocity is a zeroth-order Bessel function of the first kind:
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`Figure 4: The autocorrelation function of the 10Hz Doppler Rayleigh fading channel.
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`Level crossing rate The level crossing rate is a measure of the rapidity of the fading.
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`It
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`quantifies how often the fading crosses some threshold, usually in the positive-going direction.
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`For Rayleigh fading, the level crossing rate is:
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`√
`2πfdρe−ρ2
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`LCR =
`
`where fd is the maximum Doppler shift and ρ is the threshold level normalized to the root
`
`mean square (RMS) signal level
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`Average fade duration
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`The average fade duration quantifies how long the signal spends below the threshold . For
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`Rayleigh fading, the average fade duration is:
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`AF D =
`
`1 − e−ρ2
`LCR
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`The level crossing rate and average fade duration taken together give a useful means of
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`characterizing the severity of the fading over time.
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`Doppler power spectral density
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`The Doppler power spectral density of a fading channel describes how much spectral broad-
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`ening it causes. This shows how a pure frequency e.g. a pure sinusoid, which is an impulse
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`in the frequency domain is spread out across frequency when it passes through the channel.
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`It is the Fourier transform of the time-autocorrelation function. For Rayleigh fading with a
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`vertical receive antenna with equal sensitivity in all directions, this has been shown to be:
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`S(ν) =
`
`πfd
`
`1
`
`(cid:114)
`1 −(cid:16) ν
`
`fd
`
`(cid:17)2
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`where ν is the frequency shift relative to the carrier frequency. This equation is only valid
`for values of ν between ±fd the spectrum is zero outside this range. This spectrum is shown
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`in the figure for a maximum Doppler shift of 10 Hz. The ’bowl shape’ or ’bathtub shape’ is
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`the classic form of this Doppler spectrum.
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`• 10
`
`5
`0
`• 5
`FftQutncy shift from orritr, Htrlz
`
`10
`
`Figure 5: The normalized Doppler power spectrum of Rayleigh fading with a maximum
`Doppler shift of 10Hz.
`
`2.3 Rician Fading
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`Rician fading is a stochastic model for radio propagation anomaly caused by partial cancella-
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`tion of a radio signal by itself the signal arrives at the receiver by two different paths (hence
`
`exhibiting multipath interference), and at least one of the paths is changing (lengthening
`
`or shortening). Rician fading occurs when one of the paths, typically a line of sight signal,
`
`is much stronger than the others. In Rician fading, the amplitude gain is characterized by
`
`a Rician distribution. Rayleigh fading is the specialized model for stochastic fading when
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`there is no line of sight signal, and is sometimes considered as a special case of the more
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`generalized concept of Rician fading. In Rayleigh fading, the amplitude gain is characterized
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`by a Rayleigh distribution.
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`2.4 Further reading
`
`See references [1, 2]. The above content was based on corresponding entries of ”wikipedia,
`
`the online encyclopedia”.
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`3.0 User’s Manual
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`3.1 Requirements
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`• MATLAB version 2009b or 100% compatible. Consult the manual of your version of
`
`MATLAB for backwards compatibility, if you intend to use a more recent version of
`
`MATLAB.
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`• The Simulink package with the virtual reality toolbox installed.
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`• A version of Microsoft Windows capable of running the used MATLAB version.
`
`• Dual core CPU with 2GB RAM. Quad core CPU with 4GB RAM ensures optimal
`
`performance.
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`3.2 Installation Notes
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`The installation procedure follows that of the 1st virtual lab ”Antennas and Propagation”:
`
`• Place the provided application files in a folder that you specify, denoted as U SER DIR.
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`This folder will contain the files (.m, .fig) and folders (BaseClasses, customClasses,
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`demo, functions, java, originals, rician, slprj, texture) that comprise the application.
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`• Add the U SER DIR and all contained subfolders EXCEPT FOR THE ”ORIGINALS”
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`FOLDER to the MATLAB path. Consult the manual of your version of MATLAB for
`
`more details.
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`• Make sure that none of the application files are shadowed by same-named but irrelevant
`
`files already in the MATLAB path.
`
`It is advised to revert the MATLAB path to
`
`its factory default value before step 2, to avoid any shadowing problem. For more
`
`information on shadowing consult the manual of your version of MATLAB.
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`• Create a REG
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`SZ entry at windows registry location ’HK
`
`L
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`M/SOFTWARE/IHUvlab2’
`
`with the name ’installPath’ and content the absolute installation path of the applica-
`
`tion.
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`3.3 Application execution and usage
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`To start the application, change the current working path of MATLAB to U SER DIR and
`
`issue ”vlabs2” at the MATLAB command prompt.
`
`The simulation setup form and the 3D visualization form will appear:
`
`Figure 6: The simulation setup form.
`
`Understanding the 3D visualization and related control.
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`The 3D visualization form displays a vehicle moving on a road between two rows of buildings.
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`An transmitting antenna is placed at an arbitrary point on the plane. The car carries a re-
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`ceiving antenna. Due to the obstruction of buildings and the movement of the client/vehicle,
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`electromagnetic shadowing, fading and doppler frequency shift phenomena occur. The user
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`· ) VLABS2 • 30 viewer
`File View Viewpoints Navigation Rendering Simulation Recording Help
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`11!1~ f3
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`Figure 7: The 3D visualization form.
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`can study the effects of this phenomena on the signal reception quality, while varying the
`
`system’s geometry and signal modulation parameters in pre-specified ways.
`
`Using the menu bar, toolbar, and navigation panel on the 3D visualization form, you can
`
`• Customize the Orbisnap window
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`• Manage virtual world viewpoints
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`• Manage scene rendering
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`• Navigate in the scene
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`Menu Bar The menu bar has the following menus:
`
`• File – General file operation options, including:
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`• ++Open – Invokes a browser that you can use to browse to the virtual world you want
`
`to visualize.
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`• ++Connect to server – Allows you to connect to a Simulink 3D Animation server.
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`Enter the IP address or host name of the host computer running the Simulink 3D
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`Animation server (127.0.0.1 by default) and the port number at which the Simulink
`
`3D Animation server is listening (8124 by default).
`
`• ++Reload – Reloads the saved virtual world. Note that if you have created any
`
`viewpoints in this session, they are not retained unless you have saved those viewpoints
`
`with the Save As option.
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`• ++Save As – Allows you to save the virtual world.
`
`• ++Close – Closes the form.
`
`• View – Enables you to customize the form, including:
`
`• ++Toolbar – Toggles the toolbar display.
`
`• ++Status Bar – Toggles the status bar display at the bottom of the form. This display
`
`includes the current viewpoint, simulation time, navigation method, and the camera
`
`position and direction.
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`• ++Navigation Zones – Toggles the navigation zones on/off (see Navigation for a de-
`
`scription of how to use navigation zones).
`
`• ++Navigation Panel – Controls the display of the navigation panel, including toggling
`
`it.
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`• ++Zoom In/Out – Zooms in or out of the world view.
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`• ++Normal (100%) – Returns the zoom to normal (initial viewpoint setting).
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`• Viewpoints – Manages the virtual world viewpoints.
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`• Navigation – Manages scene navigation.
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`• Rendering – Manages scene rendering.
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`• Help – Displays the Help browser.
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`Toolbar The toolbar has buttons for some of the more commonly used operations available
`
`from the menu bar. These buttons include:
`
`• Drop-down list that displays all the viewpoints in the virtual world
`
`• Return to viewpoint button
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`• Create viewpoint button
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`• Straighten up button
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`• Drop-down list that displays the navigation options Walk, Examine, and Fly.
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`• Undo move button
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`• Zoom in/out buttons ,
`
`Navigation Panel The navigation panel has navigation controls for some of the more
`
`commonly used navigation operations available from the menu bar. These controls include:
`
`Hide panel – Toggles the navigation panel. Next/previous viewpoint – Toggles through the
`
`list of viewpoints. Return to default viewpoint – Returns focus to original default viewpoint.
`
`Slide left/right – Slides the view left or right. Navigation wheel – Moves view in one of eight
`
`directions. Navigation method – Manages scene navigation. Wireframe toggle – Toggles
`
`scene wireframe rendering. Headlight toggle – Toggles camera headlight. Help – Invokes the
`
`online help.
`
`Navigation
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`Slide left/ right
`
`~-
`
`_ Orbisnap Help
`
`Hide panel
`Next/ previous viewpoint
`
`Go to default viewpoint
`
`I \ ~
`
`Navigation met hod Wir eframe toggle
`
`Headlighttoggle
`
`Navigation wheel
`
`Figure 8: Navigation Panel.
`
`You can navigate around a virtual world using the menu bar, toolbar, navigation panel,
`
`mouse, and keyboard.
`
`Navigation view – You can change the camera position. From the menu bar, select the
`
`Navigation menu Straighten Up option. Alternatively, you can click the Straighten Up
`
`control from the toolbar or press F9 on the keyboard. This option resets the camera so that
`
`it points straight ahead.
`
`Navigation methods – Navigation with the mouse depends on the navigation method you
`
`select and the navigation zone you are in when you first click and hold down the mouse
`
`button. You can set the navigation method using one of the following:
`
`From the menu bar, select the Navigation menu Method option. This option provides three
`
`choices, Walk, Examine, or Fly. See the table Mouse Navigation. From the toolbar, select
`
`the drop-down menu that displays the navigation options Walk, Examine, and Fly. From
`
`the navigation panel, click the W, E, or F buttons. From the keyboard, press Shift+W,
`
`Shift+E, or Shift+F. Navigation zones – You can view the navigation zones for a virtual
`
`world through the menu bar or keyboard.
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