Simulate and Visualize a Land Mobile-Satellite Channel
This example shows how to model a two-state land mobile-satellite (LMS) channel model by generating a state series, its respective space series, and the channel coefficients. In a scenario involving a satellite terminal and a mobile terminal, a signal being transmitted through the channel does not always have an ideal line-of-sight path. In some cases, the signal experiences phenomena such as doppler shift, shadowing, and multipath fading. Appropriately modeling the effects of such phenomena is essential to properly design end-to-end communication links that are able to handle and compensate the effects of the channel.
An LMS channel model is used to simulate the channel envelope that is observed in a satellite-to-ground channel. Given the moving nature of the terminals, the channel envelope experiences variations due to movement of the transmitting and receiving terminals, blockage due to buildings and foliage, shadowing, and multipath.
This example models such a channel by using a two-state semi-Markov chain, where the channel alternates between a good and bad state. A good state is characterized by either line-of-sight conditions or partial shadowing conditions, whereas a bad state is characterized by either severe shadowing conditions or complete blockage.
The following block diagram shows the step-by-step procedure to model the channel:
In addition to the environment and carrier frequency defined for this example, the modeling of the channel is done by setting up the scenario. This requires defining the following parameters:
Speed of the ground terminal
Sampling rate of the channel
Azimuth orientation of the ground terminal
Initial state of the channel
Set up the channel between the satellite terminal and the mobile terminal on the ground using
p681LMSChannel System object. The channel is set to an urban scenario with 3.8 GHz carrier frequency having a mobile terminal moving at a speed of 2 m/s.
% Create an ITU-R P.681-11 channel chan = p681LMSChannel; % Environment type chan.Environment = "Urban"; % Carrier frequency (in Hz) chan.CarrierFrequency = 3.8e9; % Elevation angle with respect to ground plane (in degrees) chan.ElevationAngle = 45; % Speed of movement of ground terminal (in m/s) chan.MobileSpeed = 2; % Sampling rate (in Hz) chan.SampleRate = 400; % Direction of movement of ground terminal (in degrees) chan.AzimuthOrientation = 0;
Assign a suitable initial state for the model.
chan.InitialState = "Good";
Set the fading technique used to realize the doppler spectrum. The fading technique is either "Filtered Gaussian noise" or "Sum of sinusoids". When
FadingTechnique property is set to "Sum of sinusoids", you can also set the number of sinusoids through
chan.FadingTechnique = "Filtered Gaussian noise";
Initialize random number generator with seed. Vary the seed to obtain different channel realizations. The default value 73 is an arbitrary value.
seed = 73; chan.RandomStream = "mt19937ar with seed"; chan.Seed = seed;
Display the properties of the channel.
p681LMSChannel with properties: SampleRate: 400 InitialState: "Good" CarrierFrequency: 3.8000e+09 ElevationAngle: 45 MobileSpeed: 2 AzimuthOrientation: 0 Environment: "Urban" ChannelFiltering: true Use get to show all properties
Generate the channel for a duration of 100 seconds. Use random samples as input waveform.
% Set random number generator with seed rng(seed); % Channel duration (in s) chanDur = 100; % Random input waveform numSamples = floor(chan.SampleRate*chanDur)+1; in = complex(randn(numSamples,1),randn(numSamples,1)); % Pass the input signal through channel [fadWave,channelCoefficients,sampleTimes,stateSeries] = step(chan,in);
Visualize the power profile, the space series, and the state series generated as part of channel modeling.
Plot the power profile of input waveform and the faded waveform.
figure(1) plot(sampleTimes,20*log10(abs(in)),sampleTimes,20*log10(abs(fadWave))) title(['Power Profile of Waveform for Duration ' num2str(chanDur) ' seconds']) legend('Input Waveform', 'Faded Waveform') xlabel('Time (in s)') ylabel('Power (in dB)')
Plot the space series to show how the instantaneous power of the channel envelope varies with time.
figure(2) plot(sampleTimes,20*log10(abs(channelCoefficients))) title(['Space Series of Channel for Duration ' num2str(chanDur) ' seconds']) xlabel('Time (in s)') ylabel('Path Gain (in dB)')
Plot the state series to show how the channel state varies with time.
figure(3) plot(sampleTimes,stateSeries) title(['State Series of Channel for Duration ' num2str(chanDur) ' seconds']) axis([0 sampleTimes(end) -0.5 1.5]) xlabel('Time (in s)') ylabel('State')
This example uses
p681LMSChannel System object to generate the two-state LMS channel for the defined channel properties. You can modify the properties of the System object to observe the variations with respect to time in the power profile, channel coefficients, and state series. To model the channel for different frequency bands, you can set the parameters related to any of the data tables available in ITU-R P.681-11 Recommendation Section 3.1 Annexure 2 . You can also set the channel to custom environment with any other data set available.
 ITU-R Recommendation P.681-11 (08/2019). "Propagation data required for the design systems in the land mobile-satellite service." P Series; Radio wave propagation.