1. Simulation Model for Mobile Radio Channels Ciprian Romeo Comşa Iolanda Alecsandrescu Andrei Maiorescu Ion Bogdan ccomsa@etc.tuiasi.ro Technical University “Gh. Asachi” Iaşi Department of Telecommunications

2. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 2 2 Radio channel Diffraction Reflection Scattering Radio channel: propagation medium characterized by wave phenomena.

3. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 3 3Fading Waves are received on different propagation ways => Multi-path Propagation. The propagation is realized mostly by reflection and diffraction. The sum of waves received may have significant variations even on slow motion of receiver. short-term fadingfast fading This is called short-term fading or fast fading and follows a Rayleigh distribution. LOS propagation Diffraction Reflection

4. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 4 4Fading Waves are received on different propagation ways => Multi-path Propagation. The propagation is realized mostly by reflection and diffraction. The sum of waves received may have significant variations even on slow motion of receiver. short-term fadingfast fading This is called short-term fading or fast fading and follows a Rayleigh distribution. The mean of the received signal has slow variations on larger motion. long-term fading This is called long-term fading and follows a log-normal distribution. Short-term fading Long-term fading

5. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 5 5 Channel Modeling A channel model has to allow the evaluation of the propagation loses and theirs variations (fading). A channel model has to allow the evaluation of the propagation loses and theirs variations (fading). The Suzuki model takes into account short-term fading with superimposed long- term log-normal variations of the mean of received signal: The Suzuki model takes into account short-term fading with superimposed long- term log-normal variations of the mean of received signal:

6. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 6 6 Analytical model – Stochastic process: Extended SuzukiStochastic processLog-normal process models the short-time fading models the short-time fading is obtained considering: is obtained considering: complex zero mean Gaussian noise process complex zero mean Gaussian noise process with cross-correlated quadrature components and LOS component supposed to be independent of time (for short-time fading) LOS component supposed to be independent of time (for short-time fading) is obtained as envelope of nonzero mean Gaussian noise process is obtained as envelope of nonzero mean Gaussian noise process For particular values of environment parameters, this process follows Rice, Rayleigh or one-sided Gaussian distribution. For particular values of environment parameters, this process follows Rice, Rayleigh or one-sided Gaussian distribution.

7. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 7 7 Analytical model – Log-normal process: Extended SuzukiLog-normal processStochastic process models the long-time fading, caused by shadowing effects models the long-time fading, caused by shadowing effects is obtained from another real Gaussian noise process with zero mean and unit variance: is obtained from another real Gaussian noise process with zero mean and unit variance: m and s are two environment parameters m and s are two environment parameters and are uncorrelated and are uncorrelated

8. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 8 8 Simulation Model cross-correlated cross-correlated Simulation coefficients: Simulation coefficients: -Doppler coefficients -discrete Doppler frequencies - Doppler phases = number of sinusoids used to approximate the Gaussian processes

9. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 9 9Simulation A mixed signal simulation tool is used – Saber Designer with MAST language A mixed signal simulation tool is used – Saber Designer with MAST language MAST = HDL => the channel model can be used for simulations deeper to hardware systems MAST = HDL => the channel model can be used for simulations deeper to hardware systems Simulation Data Environment parameters: Environment parameters: Number of sinusoids: N 1 =25 and N 2 =15. Number of sinusoids: N 1 =25 and N 2 =15. Number of samples N S =10 8 and sampling period T a =3·10 -8 s. Number of samples N S =10 8 and sampling period T a =3·10 -8 s. Maximum Doppler frequency f max =91Hz, corresponding to a vehicle’s speed of 110Km/h. Maximum Doppler frequency f max =91Hz, corresponding to a vehicle’s speed of 110Km/h. Doppler coefficients c i,n and discrete Doppler frequencies f i,n are calculated at the beginning and kept constants during the simulation. Doppler coefficients c i,n and discrete Doppler frequencies f i,n are calculated at the beginning and kept constants during the simulation. Doppler phases θ i,n are modified at each simulation step given by sampling. Doppler phases θ i,n are modified at each simulation step given by sampling.

10. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 10 10 Simulation results (1) Envelope of the simulated extended Suzuki process

11. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 11 11 Simulation results (2) The differences between the generated signal distribution obtained as histogram and the analytical pdf are hardly observable. The differences between the generated signal distribution obtained as histogram and the analytical pdf are hardly observable. The values for mean and standard deviation confirms this affirmation. The values for mean and standard deviation confirms this affirmation.

12. July, 2002 Technical University “Gh. Asachi” Iaşi Department of Telecommunications Slide 12 12Conclusion Histogram of simulated extended Suzuki model, in cases of: Light shadowing  log-normal distribution Light shadowing  log-normal distribution Heavy shadowing  Rice (or Rayleigh) distribution Heavy shadowing  Rice (or Rayleigh) distribution