Wireless Communication Channels

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41st IEEE CDC Las Vegas, Nevada December 9th 2002
Workshop M-5 Wireless Communication Channels
Modeling, Analysis, Simulations and
Applications 
Organizers Charalambos D. Charalambous Nickie
Menemenlis
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Wireless Communication Channels

• Schedule
• 0800-0845 Introduction to Wireless
  Communication Channels (C.D. Charalambous)
• 845-915 Statistical Analysis of Wireless Fading
  Channels (C.D. Charalambous)
• 915-925 Break
• 925 -1010 Stochastic Differential Equations in
  Modeling Log-Normal Shadowing (N. Menemenlis)
• 1010-1055 Stochastic Differential Equations in
  Modeling Short-Term Fading (N. Menemenlis)
• 1055-1100 Break
• 1100-1200 Applications (C.D. Charalambous)
• Additional information can be found at
• http//www.site.uottawa.ca/chadcha/CDC2002

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Introduction to Wireless Communication Channels

• Shannons communication channel
• Impulse response of wireless fading channels
• Large-scale and small scale propagation models
• Log-Normal shadowing channel
• Short-term fading channel
• Autocorrelation functions and power spectral
  densities
• Assumption WSSUS
• Time spreading
• Time variations
• Channel classification
• Channel simulations

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Chapter 1 Shannons Wireless Communication System
Channel code word
Message Signal
Modulated Transmitted Signal
Source
Source Encoder
Channel Encoder
Mod- ulator
Wireless Channel
User
Source Decoder
Channel Decoder
Demod- ulator
Received Signal
Estimate of Message signal
Estimate of channel code word
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Chapter 1 Large and Small Scale Propagation
Models
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Chapter 1 Wireless Communication System
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Chapter 1 Impulse Response Characterization

• Impulse response Time-spreading multipath
• and time-variations time-varying environment

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Chapter 1 Multipath Fading Components

• Complex low-pass representation of impulse
  response

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Chapter 1 Band-pass Representation of Impulse
Response

• Band-pass representation of impulse response

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Chapter 1 Representation of Additive Noise
Channel

• Low-pass and band-pass representation of received
  signal

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Chapter 1 Large and Small Scale Propagation
Models

• Large scale propagation models
• T-R separation distances are large
• Main propagation mechanism reflections
• Attenuation of signal strength due to power loss
  along distance traveled shadowing
• Distribution of power loss in dBs Log-Normal
• Log-Normal shadowing model
• Fluctuations around a slowly
• varying mean

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Chapter 1 Large and Small Scale Propagation
Models

• Small scale propagation
• T-R separation distances are small
• Heavily populated, urban areas
• Main propagation mechanism scattering
• Multiple copies of transmitted signal arriving at
  the transmitted via different paths and at
  different time-delays, add vectotrially at the
  receiver fading
• Distribution of signal attenuation
• coefficient Rayleigh, Ricean.
• Short-term fading model
• Rapid and severe signal
• fluctuations around a slowly
• varying mean

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Chapter 1 Log-Normal Shadowing Model
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Chapter 1 Log-Normal Shadowing Model

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Chapter 1 Log-Normal Shadowing Model

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Chapter 1 Log-Normal Shadowing Model

• Power path-loss in dBs, x, and Distributions x
  normal and attenuation coefficient, r, vs d
  rekx log-normal

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Chapter 1 Short-Term Fading Model

• 3-Dimensional Model Clarke 68, Aulin 79

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Chapter 1 Short-Term Fading Model

• 3-D Model Clarke 68, Aulin 79
• Transmitted signal Reejwct
• Total field at mobile, or receiving location,
  O(x0, y0, z0)

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Chapter 1 Short-Term Fading Model

• 3-D Model Clarke 68, Aulin 79
• Total field at receiving location when mobile
  moves
• O(x0, y0, z0) gt (x0vtcosg, y0 vtsing, z0),
  v velocity of mobile

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Chapter 1 Short-Term Fading Model

• 3-D Model Clarke 68, Aulin 79
• Statistical characterization of I(t), Q(t)

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Chapter 1 Short-Term Fading Model

• Statistical characterization of rn

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Chapter 1 Short-Term Fading Model

• Autocorrelation functions

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Chapter 1 Short-Term Fading Model

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Chapter 1 Time Delays of Paths

• Complex low-pass representation of impulse
  response
• Typically the time delays are modeled using
  exponential distribution, implying that the
  number of paths is a Poisson counting process
• In reality this representation is not very
  accurate.

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Chapter 1 Channel Autocorrelation Functions

• General expressions for the Autocorrelation
  function are introduced by Bello 63 for a widely
  accepted Wide-Sense Stationary Uncorrelated
  Scattering (WSSUS) channel
• WSS in the time-domain
• US attenuation and phase shift of paths i and j
  are uncorrelated

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Chapter 1 Channel Autocorrelation Functions

• Time-spreading Multipath characteristics of
  channel

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Chapter 1 Channel Autocorrelation Functions

• Time-spreading Multipath characteristics of
  channel

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Chapter 1 Channel Autocorrelation Functions

• Time-spreading Multipath characteristics of
  channel
• Multi-path delay spread, Tm
• Characterizes time dispersiveness of the channel,
• Obtained from power delay-profile, Fc(t)
• Indicates delay during which the power of the
  received signal is above a certain value.
• Coherence bandwidth, Bc approx. 1/ Tm
• Indicates frequencies over which the channel can
  be considered flat
• Two sinusoids separated by more than Bc affected
  differently by the channel
• Indicates frequency selectivity during
  transmission.

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Chapter 1 Channel Autocorrelation Functions

• Time variations of channel Frequency-spreading

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Chapter 1 Channel Autocorrelation Functions

• Time variations of channel Frequency-spreading

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Chapter 1 Channel Autocorrelation Functions

• Time variations of channel Frequency-spreading
• Doppler Spread, Bd
• Characterizes frequency dispersiveness of the
  channel, or the spreading of transmitted
  frequency due to different Doppler shifts
• Obtained from Doppler spectrum, Sc(l)
• Indicates range of frequencies over which the
  received Doppler spectrum is above a certain
  value
• Coherence time, Tc approx. 1/ Bd
• Time over which the channel is time-invariant
• A large coherence time Channel changes slowly

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Chapter 1 Channel Autocorrelation Functions
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Chapter 1 Channel Classification

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Chapter 1 Channel Classification

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Chapter 1 Channel Classification

• Underspread channel TmBd ltlt 1
• Channel characteristics vary slowly (Bd small)
  or paths obtained within a short interval of time
  (Tm small).
• Easy to extract channel parameters.
• Overspread channel TmBd gtgt 1
• Hard to extract parameters as channel
  characteristics vary fast and channel changes
  before all paths can be obtained.

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Chapter 1 Flat Fading Channel Simulations

• Flat Fading
• a(t) Rayleigh or Ricean

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Chapter 1 Frequency Selective Channel Simulations

• Frequency Selective

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Chapter 1 References

• G.L. Turin. Communication through noisy,
  random-multipath channels. IRE Convention Record,
  pp. 154-166, 1956.
• P. Bello. Characterization of random time-variant
  linear channels. IEEE Transactions in
  Communications, pp 360-393, 1963.
• J.F. Ossanna. A model for mobile radio fading
  due to building reflections Theoretical and
  experimental waveform power spectra. Bell Systems
  Technical Journal, 432935-2971, 1964.
• R.H. Clarke. A statistical theory of mobile radio
  reception. Bell Systems Technical Journal,
  47957-1000, 1968.
• M.J Gans. A power-spectral theory of propagation
  in the mobile-radio environment. IEEE
  Transactions on Vehicular Technology,
  VT-21(1)27-38, 1972.
• H. Suzuki. A statistical model for urban radio
  propagation. IEEE Transactions in Communications,
  25673-680, 1977.
• T. Aulin. A modified model for the fading signal
  at a mobile radio channel. IEEE Transactions on
  Vehicular Technology, VT-28(3)182-203, 1979.
• A.D.Saleh, R.A.Valenzuela. A statistical model
  for indoor multi-path propagation. IEEE Journal
  on Selected Areas in Communications,
  5(2)128-137, 1987.

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Chapter 1 References

• M. Gudamson. Correlation model for shadow fading
  in mobile radio systems. Electronics Letters,
  27(23)2145-2146, 1991.
• D. Giancristofaro. Correlation model for shadow
  fading in mobile radio channels. Electronics
  Letters, 32(11)956-958, 1996.
• A.J. Coulson, G. Williamson, R.G. Vaughan. A
  statistical basis for log-normal shadowing
  effects in multipath fading channels. IEEE
  Transactions in Communications, 46(4)494-502,
  1998.
• E. Biglieri, J. Proakis, S. Shamai. Fading
  channels Information-theoretic and communication
  aspects. IEEE Transactions on Information Theory,
  44(6)2619-2692, October 1998.
• W.C.Jakes. Microwave mobile communications, New
  York, Wiley-Interscience, 1974.
• K. Pahlavan, A.H. Levesque. Wireless Information
  Networks, New York, Wiley-Interscience, 1995.
• J.G. Proakis. Digital Communications,
  Mc-Graw-Hill, New-York, 1995.
• T.S. Rappaport. Wireless Communications, Prentice
  Hall, 1996.