Modeling of Indoor Radio Channel - PowerPoint PPT Presentation

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Modeling of Indoor Radio Channel

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is Rayleigh. distributed. Baseband impulse response model. Summary ... uniform phases, and independent Rayleigh amplitudes with variances that decay ... – PowerPoint PPT presentation

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Title: Modeling of Indoor Radio Channel


1
Modeling of Indoor Radio Channel
  • Weerachai Anotaipaiboon
  • Professor Bob Brodersen
  • Dept. of EECS
  • University of California, Berkeley

2
Modeling of Indoor Radio Channel
  • A well characterized multipath medium is useful
    in designing the transmitter and receiver that
    can reduce the effect of multipath fading
  • A simple statistical multipath model of the
    indoor radio channel that fits the measurements
    well is presented
  • Future work modeling of time-variant indoor
    radio channel

3
Baseband Impulse Response
Where
The parameters can be treated as time-invariant
random variables since the variation rates are
very slow compared to any useful signaling rate
that are likely to be considered.
4
Magnitude Impulse Response
Typical Impulse Response
h(t,?)
t
Impulse Response Model
t
5
Parameter Models
Tl is exponentially distributed with parameter ?
?kl is exponentially distributed with parameter ?
?l, ?kl ? Uniform(0,2?)
6
Parameter Models (Continue)
is exponentially distributed which implies that
is Rayleigh
distributed.
Baseband impulse response model
7
Summary
  • With this model, the received signal rays arrive
    in clusters
  • The rays have uniform phases, and independent
    Rayleigh amplitudes with variances that decay
    exponentially with cluster and ray delays
  • The clusters and the rays within each cluster
    form Poisson arrival processes with different,
    but fixed, rates

8
Summary (continue)
  • The clusters are formed by the building
    superstructure, while the individual rays are
    formed by objects in the vicinities of the
    transmitter and the receiver

9
Future Work
  • Analysis of the indoor propagation channels
    temporal variation
  • Model the channel as a linear time-varying filter
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