Presentation on theme: "Data Communication lecture101 Channel Models. Data Communication lecture102 Introduction Propagation models are fundamental tools for designing any broadband."— Presentation transcript:
Data Communication lecture101 Channel Models
Data Communication lecture102 Introduction Propagation models are fundamental tools for designing any broadband wireless communication system. A propagation model basically predicts what will happen to the transmitted signal while in transit to the receiver Traditionally, ‘propagation models’ is the term applied to those algorithms and methods used to predict the median signal level at the receiver. Such models include signal level information, signal time dispersion information and, in the case of mobile systems, models of Doppler shift distortions arising from the motion of the mobile.
Data Communication lecture103 Fading Fluctuation in the strength of signal, because of variations in the transmission medium. Fading is a broad term applied to a wide range of variation in the signal amplitude, phase, and frequency characteristic. For example, the term ‘shadow fading‘ is used to describe the decrease in signal strength that is observed when a mobile terminal is behaind a building.
Data Communication lecture104 Slow (S) and fast fading (a) in Cellular channel
Data Communication lecture105 Propagation mechanisms A: free space B: reflection C: diffraction D: scattering A: free space B: reflection C: diffraction D: scattering reflection: object is large compared to wavelength scattering: object is small or its surface irregular
Data Communication lecture106 Radio channel modelling Narrowband Models Because the signal bandwidth is narrow, the fading mechanism will affect all frequencies in the signal passband equally. So, a narrowband channel is often referred to as a flat-fading channel. Wideband Models The bandwidth of the signal, sent through the channel is such that time dispersion information is required. Time dispersion causes the signal fading to vary as a function of frequency, so wideband channels are often called frequency- selective fading channels.
Data Communication lecture107 Comparison Narrowband modelling Wideband modelling Deterministic models (e.g. ray tracing, playback modelling) Deterministic models (e.g. ray tracing, playback modelling) Stochastical models Calculation of path loss e.g. taking into account - free space loss - reflections - diffraction - scattering Calculation of path loss e.g. taking into account - free space loss - reflections - diffraction - scattering Basic problem: signal fading Basic problem: signal dispersion
Data Communication lecture108 Signal fading in a narrowband channel magnitude of complex-valued radio signal distance propagation paths fade signal replicas received via different propagation paths cause destructive interference Tx Rx
Data Communication lecture109 Low-pass equivalent (LPE) signal Real-valued RF signal Complex-valued LPE signal RF carrier frequency In-phase signal component Quadrature component
Data Communication lecture1010 Fading: illustration in complex plane in-phase component quadrature phase component Tx Rx Received signal in vector form: resultant (= summation result) of “propagation path vectors” Wideband channel modelling: in addition to magnitudes and phases, also path delays are important. path delays are not important
Data Communication lecture1011 Generic Wideband Channel Model Wideband generally indicates those channels in which time dispersion and frequency-selective fading have a significant impact on the signal being transmitted. For signals whose occupied bandwidth is narrow compared to the correlation bandwidth of the channel, the generic wideband model simplifies to a narrowband model in which many elements of the wideband model may be discarded.
Data Communication lecture1012 If the channel is considered as a filter with some low- pass impulse response, then that impulse response would be given by:
Data Communication lecture1013 A sinewave signal at frequency ω leaving the transmitting antenna would arrive at the receiver reduced in amplitude by factor A, shifted in phase by θ, and delayed by τ seconds. Such a model of the transmission channel is applicable for free-space propagation conditions in which signal energy arrives at the receiver directly (via one path) from the transmitter.
Data Communication lecture1014 If the channel consisted of two transmission paths for the transmitted energy to arrive at the receiver (for example, with the addition of a single ground reflection), the channel impulse response would be the sum of the effect of the two paths: This is the impulse response of the so-called ‘two-ray’ channel model.
Data Communication lecture1015 For N possible transmission paths, h(t) becomes: This is the channel impulse response to a particular point p 2 (x 2, y 2, z 2 ) from a transmitter located at point p 1 (x 1, y 1, z 1 ). LOS path
Data Communication lecture1016 Example: multipath signal The received multipath signal is the sum of N attenuated, phase shifted and delayed replicas of the transmitted signal s ( t ) T TmTm Normalized delay spread D = T m / T :
Data Communication lecture1017 Important Note: The normalized delay spread is an important quantity. When D << 1, the channel is - narrowband - frequency-nonselective - flat and there is no intersymbol interference (ISI). When D approaches or exceeds unity, the channel is - wideband - frequency selective - time dispersive
Data Communication lecture1018 BER vs. S/N performance Typical BER vs. S/N curves S/N BER Frequency-selective channel (no equalization) Flat fading channel Gaussian channel (no fading) In a Gaussian channel (no fading) BER Q ( S/N ) erfc ( S/N )
Data Communication lecture1019 BER vs. S/N performance Typical BER vs. S/N curves S/N BER Frequency-selective channel (no equalization) Flat fading channel Gaussian channel (no fading) Flat fading: NB channel z = signal power level
Data Communication lecture1020 BER vs. S/N performance Typical BER vs. S/N curves S/N BER Frequency-selective channel (no equalization) Flat fading channel Gaussian channel (no fading) Frequency selective fading irreducible BER floor
Data Communication lecture1021 Ray-Tracing Propagation Model
Data Communication lecture1022 Measured power delay profile.
Data Communication lecture1023 RMS Delay spread A common measure of the amount of time dispersion in a channel is the RMS delay spread. The RMS delay spread can be found from the power delay profile:
Data Communication lecture1024 The more general impulse response can thus be written as: Here, the number, amplitude, phase, and time delay of the components of the summation are a function of the location of the transmit and receive antenna points in the propagation space. This equation is for a single static point in space. Generic Model, Continue
Data Communication lecture1025 For mobile communication, the receiver is often moving. That motion can affect the phase relationship of the components of this equation, in a way that may be important to data symbols being transmitted. This motion will result in a frequency or Doppler shift of the received signal, which will be a function of speed and direction of motion, and the angle of arrival (AOA) of the signal energy.
Data Communication lecture1026 Modification to include the Doppler shift: Here, Δθ n is a phase displacement due to the motion.
Data Communication lecture1027 For a mobile receiver: φ n is the arrival angle of the n th component, v is the speed of motion, φ v is the direction of motion, and λ is the wavelength. Doppler Shift
Data Communication lecture1028 Physical interpretation of Doppler shift V arriving path direction of receiver movement Rx Maximum Doppler shift Angle of arrival of arriving path with respect to direction of movement V = speed of receiver = RF wavelength V = speed of receiver = RF wavelength Doppler frequency shift
Data Communication lecture1029 In general, the amplitudes A n and phase shifts θ n, will be functions of the carrier frequency ω, thus:
Data Communication lecture1030 Time-Variant Channels To deal with a time-variant channel, we define the input delay-spread function h(t, τ ). This is the low-pass response of the channel at some time t to a unit impulse function input at some previous time τ seconds earlier. Note that this delay τ is different from the discrete τ 1, τ 2... τ n arrival delay times, that define when the signal waves reach the receiver.
Data Communication lecture1031 Time-Variant Channels time t h(t,) h(t,) delay Channel is assumed linear!
Data Communication lecture1032 Time-Variant Channels The output of the channel y(t) can then be found by the convolution of the input signal u m (t) with h(t, τ ) integrated over the delay variable τ:
Data Communication lecture1033
Data Communication lecture1034
Data Communication lecture1035 Some Notes Using an impulse response from a ray-tracing propagation model, and convolving it with a raised cosine symbol pulse, the result is a time signature of the channel. The variations in signatures are due to the relative phase changes, and not changing amplitudes. By taking the Fourier Transform of the time signatures, it is possible to created spectrum signatures. The nonuniform frequency response, represents the frequency-selective nature of the channel.
Data Communication lecture1036 Path Loss Modeling Maxwell’s equations –Complex and impractical Physical Models –Free space path loss model Too simple –Ray tracing models Requires site-specific information Empirical Models –Don’t always generalize to other environments
Data Communication lecture1037 Empirical Models Commonly used in cellular system simulations Are based on observations or measurements. measurements are typically done in the field to measure path loss, delay spread, or other channel characteristics. Site and field dependent
Data Communication lecture1038 Empirical Models IEEE (SUI) model where d is the distance in meters, d 0 = 100 meters, h b is the base station height above ground (10m < h b < 80 m)
Data Communication lecture1039
Data Communication lecture1040
Data Communication lecture1041 Some Other Empirical Models Okumura model –Empirically based (site/freq specific) Hata model –Analytical approximation to Okumura model Cost 136 Model: –Extends Hata model to higher frequency (2 GHz) Walfish/Bertoni: –Cost 136 extension to include diffraction from rooftops
Data Communication lecture1042 Physical Models
Data Communication lecture1043 Free Space (LOS) Model Path loss for unobstructed LOS path Power falls off : –Proportional to d 2 –Proportional to 2 ( inversely proportional to f 2 ) d=vt
Data Communication lecture1044 Two Path Model Path loss for one LOS path and 1 ground (or reflected) bounce Ground bounce approximately cancels LOS path above critical distance Power falls off –Proportional to d 2 (small d) –Proportional to d 4 (d>d c )
Data Communication lecture1045 Simplified Path Loss Model Used when path loss dominated by reflections. Most important parameter is the path loss exponent , determined empirically.
Data Communication lecture1046 Ray Tracing Approximation Represent wavefronts as simple particles Geometry determines received signal from each signal component Typically includes reflected rays, can also include scattered and defracted rays. Requires site parameters –Geometry –Dielectric properties
Data Communication lecture1047 General Ray Tracing Models all signal components –Reflections –Scattering –Diffraction Requires detailed geometry and dielectric properties of site –Similar to Maxwell, but easier math. Computer packages often used
Data Communication lecture1048
Data Communication lecture1049
Data Communication lecture1050
Data Communication lecture1051 Simplified indoor model SIM An effort to provide a fast and simple model that predicts indoor signal levels. Worksin the area of 2.4 GHz Wi-Fi or 5.7 GHz U-NII band systems, intended to work over short ranges, especially indoors through walls and floors. SIM makes use of four basic propagation primitives: line-of-sight rays, wall transmission loss, corner diffraction, and attenuation due to partial Fresnel zone obstruction