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Institute of information & Communication Technology (IICT), MUET

Institute of Information & Communication Technologies (I2CT)Mehran University of Engineering & Technology, Jamshoro, Pakistan

ADVANCED SIMULATION TOOLS

Lab 06 Roll Number _______________

Rician Fading Channel Simulations

6.1 Performance Objectives

After this lab, you should be able to:

Acquire basic understanding of Rician Fading

Be able to generate noise signal with Rician effect.

Be able to analyze the effect of Rician Fading in Simulink

6.2 Equipment Required

PC with Windows

MATLAB 6.5 or latest with Signal Processing and Communication Toolbox

6.3 Introduction to Multipath Channel Environment

6.3.1 Rician Fading

The previous lab we simulated the multipath propagation channel without LOS and observed the BER

performance under Rayleigh fading channel for different values of Doppler shift and its affect on the

constellation diagram of the modulated signal.

In this lab, we shall simulate Rician fading, where there is a LOS component present alongside multipath

components.

Following table will help you choose realistic parameters for simulation

Path delay

By convention, the first delay is typically set to zero and corresponds

to the first arriving path

For indoor environments, path delays after the first are typically

between 1 ns and 100 ns

For outdoor environments, path delays after the first are typicallybetween 100 ns and 10 s

Path gain

The average path gains in the channel object indicate the average

power gain of each fading path. In practice, an average path gain value

is a large negative dB value. However, computer models typically use

average path gains between -20 dB and 0 dB

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Doppler shift Doppler shift can be found out using the speed of the mobile and the

operating frequency using relation

Fd = vf/c

where a Doppler shift of 0 corresponds to a static channel

K-factor The Rician K-factor specifies the ratio of specular-to-diffuse power for

a direct line-of-sight path. The ratio is expressed linearly, not in dBA K-factor of 0 corresponds to Rayleigh fading

Table 6.1: Parameters for Rician channel object

6.3.2 Modeling Rician Fading in MATLAB

chan = ricianchan(ts,fd,k) constructs a frequency-flat ("single path") Rician fading channel object. ts is

the sample time of the input signal, in seconds. fd is the maximum Doppler shift, in Hertz. k is the Rician

K-factor. In this channel, the specular component has zero phase and the phase does not change with

the Doppler shift. You can model the effect of the channel on a signal x by using the syntax y =

filter(chan,x).

chan = ricianchan(ts,fd,k,tau,pdb) constructs a frequency-selective ("multiple path") fading channel

object that models the first discrete path as a Rician fading process and each of the remaining discrete

paths as an independent Rayleigh fading process. tau is a vector of path delays, each specified in

seconds. pdb is a vector of average path gains, each specified in dB.

chan = ricianchan constructs a frequency-flat channel object with no Doppler shift and a K-factor of 1.

This is a static channel. The sample time of the input signal is irrelevant for frequency-flat static

channels.

6.3.3 Quasi-static Channel Modeling

The example below illustrates the quasi-static channel modeling approach.

M = 4; % DQPSK modulation order

numBits = 10000; % Each trial uses 10000 bits.

numTrials = 20; % Number of BER computations

% Create Rician channel object.

chan = ricianchan; % Static channel

chan.KFactor = 10; % Rician K-factor

% Because chan.ResetBeforeFiltering is 1 by default,

% FILTER resets the channel in each trial below.

% Compute error rate once for each independent trial.

for n = 1:numTrials

tx = randint(numBits,1,M); % Random bit stream

dpskSig = dpskmod(tx,M); % DPSK signal

fadedSig = filter(chan, dpskSig); % Effect of channel

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rxSig = awgn(fadedSig,20); % Add Gaussian noise.

rx = dpskdemod(rxSig,M); % Demodulate.

% Compute number of symbol errors.

% Ignore first sample because of DPSK initial condition.

nErrors(n) = symerr(tx(2:end),rx(2:end))

end

per = mean(nErrors > 0) % Proportion of packets that had errors

6.3.4 Simulink Model

A wireless system is supposed to transmit data using BPSK modulation. Test the system for BER

performance and scatter plots under AWGN and Rician fading environment.

Figure 1: Simulink Model for BPSK over AWGN and Rician channel

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Review Questions

1. Define the term Doppler shift?

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2. What is the Difference between Static channel and Quasi-Static channel?

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3. What parameters you have to change to model Rayleigh channel effect with rician

block?

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4. A demonstration for this experiment was given in Simulink environment, with BPSK

under Rician and AWGN environment. Build another Simulink model with differential D-

QPSK and discuss the difference in results based on some plots.

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