Time variance of uwb channels

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Time variance of UWB channels

  • Andreas F. Molisch


  • Introduction

  • Movement of TX/RX

  • Movement of scatterers

  • Implementation issues

  • Impact on system evaluation

  • Summary and conclusions


  • Current status of model:

    • SV model – uses several clusters
    • Distinction between small-scale and large-scale statistics
    • 4 different environments (LOS, NLOS)
  • Temporal variations of channel not yet defined

Basic modeling approach

  • Two causes of temporal variation:

    • TX/RX movement
    • Scatterer movement (shadowing)
  • Different modeling approaches:

TX-RX movement

  • WSSUS model (Bello 1963)

  • Angular spectrum Doppler spectrum

  • Doppler spectrum temporal autocorrelation

  • Fourier transformation

Angular spectrum

  • Simple model for angular spectrum: rectangular (instead of Laplacian)

  • Angular spread increases with delay

  • Total angular spread: 38 degree [Cramer et al. 2002]

Moving scatterers

  • Model scenario: person moving through LOS

    • On straight line 80cm from receiver
    • Person modeled as cylinder with 40cm radius
    • No transmission through or diffraction around scatterer considered
  • Shadowing certain angular region

  • Means different attenuation for different delays

Implementation recipe (I)

  • TX/RX movement:

    • Compute ACF for each delay from angular spectrum
    • Generate iid random variables
    • Filter (FFT implementation most efficient)
    • “standard” implementations for Rayleigh fading do not work

Implementation recipe (II)

  • Scatterer movement

    • Geometrical approach
    • At discrete position of scatterers:
    • Linear interpolation between discrete scatterer positions

Impact on system evaluation

  • Current suggestion: independent channel realization for each data block

  • Other extreme case: no temporal variations

  • Why smooth transitions required?

    • Channel tracking and synchronization
    • How long are outages (needs application model)
    • Smart antennas


  • Simple model for temporal variations

  • Two cases:

    • RX/TX movement, use WSSUS model
    • Person walking through LOS; use geometrical approach
  • Suggestion for system evaluation:

    • All proposals: with independent data blocks and complete coherence
    • For system with trackers (if desired by proponent): continuous model

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