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function [sim_param, sim_state] = CmlPlot( varargin )
% CmlPlot plots simulation results
%
% The calling syntax is:
% [sim_param, sim_state] = CmlPlot( scenario_filename, cases )
%
% Outputs:
% sim_param = A structure containing simulation parameters.
% sim_state = A structure containing the simulation state.
% Note: See readme.txt for a description of the structure formats.
%
% Required inputs:
% scenario_filename = the name of the file containing an array of sim_param structures.
% cases = a list of the array indices to plot.
%
% Note: Multiple scenario files can be specified. In this case, the argument list
% should contain each scenario file to be used followed by the list of array indices
% to read from that file.
%
% Example:
% [sim_param, sim_state] = CmlPlot( 'Scenario1', [1 2 5], 'Scenario2', [1 4 6] );
%
% Copyright (C) 2005-2006, Matthew C. Valenti
%
% Last updated on June 4, 2006
%
% Function CmlPlot is part of the Iterative Solutions Coded Modulation
% Library (ISCML).
%
% The Iterative Solutions Coded Modulation Library is free software;
% you can redistribute it and/or modify it under the terms of
% the GNU Lesser General Public License as published by the
% Free Software Foundation; either version 2.1 of the License,
% or (at your option) any later version.
%
% This library is distributed in the hope that it will be useful,
% but WITHOUT ANY WARRANTY; without even the implied warranty of
% MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
% Lesser General Public License for more details.
%
% You should have received a copy of the GNU Lesser General Public
% License along with this library; if not, write to the Free Software
% Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA
% setup structures are retrieve data
% give an extra argument to force sim_param.reset = 0
[sim_param, sim_state] = ReadScenario( varargin{:}, [] );
number_cases = length( sim_param );
% determine the simulation types
sim_types = zeros( 8, number_cases );
for ( case_number=1:number_cases )
if ( strcmp( sim_param(case_number).sim_type, 'capacity' ) )
sim_types(1,case_number) = 1; % capacity simulation
elseif ( strcmp( sim_param(case_number).sim_type, 'exit' ) )
sim_types(2,case_number) = 1; % EXIT
elseif ( strcmp( sim_param(case_number).sim_type, 'uncoded' ) )
sim_types(3,case_number) = 1; % uncoded modulation
elseif ( strcmp( sim_param(case_number).sim_type, 'coded' ) )
sim_types(4,case_number) = 1; % coded modulation
elseif ( strcmpi( sim_param(case_number).sim_type, 'outage' )|strcmpi( sim_param(case_number).sim_type, 'bloutage' ) )
sim_types(5,case_number) = 1; % outage probability
elseif ( strcmp( sim_param(case_number).sim_type, 'throughput' ) )
sim_types(6,case_number) = 1; % throughput of hybrid-ARQ
elseif ( strcmp( sim_param(case_number).sim_type, 'bwcapacity' ) )
sim_types(7,case_number) = 1; % capacity of FSK under BW constraint
elseif ( strcmp( sim_param(case_number).sim_type, 'minSNRvsB' ) )
sim_types(8,case_number) = 1; % Min SNR as a function of B
end
end
fig_number = 0;
% first plot capacity vs. Eb/No and Es/No, if there are any capacity curves requested
if ( sum( sim_types(1,:) ) )
fig_number = fig_number + 1;
figure( fig_number );
for (i=find( sim_types(1,:) == 1 ) )
EsNo = 10.^(sim_param(i).SNR/10); % assume SNR is Es/No in dB
EbNo = EsNo./(sim_state(i).capacity_avg*log2(sim_param(i).mod_order));
EbNodB = 10*log10( EbNo );
plot( EbNodB, log2(sim_param(i).mod_order)*sim_state(i).capacity_avg, sim_param(i).linetype );
hold on;
end
% compute unconstrained (Gaussian input) capacity
EsNodB = sim_param(i).SNR;
EsNo = 10.^(EsNodB/10);
cap_unconstrained = log2(1+EsNo);
EbNo = EsNo./cap_unconstrained;
EbNodB = 10*log10( EbNo );
legend( sim_param( find( sim_types(1,:) == 1 ) ).legend );
% uncomment if you want to show unconstrained
% plot( EbNodB, cap_unconstrained, '-.');
% legend( sim_param( find( sim_types(1,:) == 1 ) ).legend, 'Unconstrained', 2 );
xlabel( 'Eb/No in dB' );
ylabel( 'Capacity' );
hold off;
% Eb/No vs. Capacity (useful for FSK modulation)
fig_number = fig_number + 1;
figure( fig_number );
for (i=find( sim_types(1,:) == 1 ) )
EsNo = 10.^(sim_param(i).SNR/10); % assume SNR is Es/No in dB
EbNo = EsNo./(sim_state(i).capacity_avg*log2(sim_param(i).mod_order));
EbNodB = 10*log10( EbNo );
plot( sim_state(i).capacity_avg, EbNodB, sim_param(i).linetype );
hold on;
end
ylabel( 'Eb/No in dB' );
xlabel( 'Rate' );
hold off;
% plot capacity vs. Es/No
fig_number = fig_number + 1;
figure( fig_number );
for (i=find( sim_types(1,:) == 1 ) )
plot( sim_param(i).SNR, log2(sim_param(i).mod_order)*sim_state(i).capacity_avg, sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(1,:) == 1 ) ).legend );
% uncomment if you want to show unconstrained
% plot( EsNodB, cap_unconstrained, '-.');
% legend( sim_param( find( sim_types(1,:) == 1 ) ).legend, 'Unconstrained', 2 );
xlabel( 'Es/No in dB' );
ylabel( 'Capacity' );
hold off;
end
% next plot BER vs. Eb/No if this is a coded or uncoded simulation
if ( sum( sum( sim_types(3:4,:) ) ) )
% plot BER vs. Eb/No
fig_number = fig_number + 1;
figure( fig_number );
% BER of uncoded modulation
for (i=find( sim_types(3,:) == 1 ) )
% Can only plot against Eb/No (add logic later)
if ( sim_param(i).SNR_type(2) ~= 'b' )
error( 'Uncoded modulation results must use SNR_type of Eb/No in dB' );
end
figure( fig_number );
semilogy( sim_param(i).SNR, sim_state(i).BER, sim_param(i).linetype );
hold on;
end
% BER of coded modulation
for (i=find( sim_types(4,:) == 1 ) )
% Convert to Eb/No (dB) if stored as Es/No (dB)
if ( sim_param(i).SNR_type(2) ~= 'b' )
% This is Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
else
EbNodB = sim_param(i).SNR;
end
% only plot the last iteration
if ( length( sim_param(i).max_iterations ) )
max_iter = sim_param(i).max_iterations;
else
max_iter = 1;
end
semilogy( EbNodB, sim_state(i).BER( max_iter, : ), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(3,:) == 1 ) ).legend, sim_param( find( sim_types(4,:) == 1 ) ).legend, 0 );
xlabel( 'Eb/No in dB' );
ylabel( 'BER' );
for (i=find( sim_types(4,:) == 1 ) )
if ( length( sim_param(i).plot_iterations ) )
% Convert to Eb/No (dB) if stored as Es/No (dB)
if ( sim_param(i).SNR_type(2) ~= 'b' )
% This is Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
else
EbNodB = sim_param(i).SNR;
end
% plot the other iterations
semilogy( EbNodB, sim_state(i).BER(sim_param(i).plot_iterations,:), sim_param(i).linetype );
end
end
hold off;
% Now plot against Es/No, if uncoded
if sum( sim_types(4,:) )
fig_number = fig_number + 1;
figure( fig_number );
for (i=find( sim_types(4,:) == 1 ) )
% see if Es/No is defind, otherwise derive
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
% Convert to Es/No
EbNo = 10.^(EbNodB/10);
EsNo = sim_param(i).rate*EbNo;
EsNodB = 10*log10(EsNo);
else
% This is already in Es/No
EsNodB = sim_param(i).SNR;
end
% only plot the last iteration
if ( length( sim_param(i).max_iterations ) )
max_iter = sim_param(i).max_iterations;
else
max_iter = 1;
end
% Plot FER versus Es/No in dB
figure( fig_number );
semilogy( EsNodB, sim_state(i).BER( max_iter, : ), sim_param(i).linetype );
hold on;
end
figure( fig_number );
legend( sim_param( find( sim_types(4,:) == 1 ) ).legend, 0 );
xlabel( 'Es/No in dB' );
ylabel( 'BER' );
for (i=find( sim_types(4,:) == 1 ) )
if ( length( sim_param(i).plot_iterations ) )
% see if Es/No is defind, otherwise derive
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
% Convert to Es/No
EbNo = 10.^(EbNodB/10);
EsNo = sim_param(i).rate*EbNo;
EsNodB = 10*log10(EsNo);
else
% This is Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
end
% plot the other iterations
figure( fig_number );
semilogy( EsNodB, sim_state(i).BER(sim_param(i).plot_iterations,:), sim_param(i).linetype );
end
end
figure( fig_number );
hold off;
end
end
% Plot the SER if uncoded
if ( sum( sum( sim_types(3,:) ) ) )
% plot SER vs. Eb/No
fig_number = fig_number + 1;
figure( fig_number );
% SER of uncoded modulation
for (i=find( sim_types(3,:) == 1 ) )
% Convert to Eb/No (dB) if stored as Es/No (dB)
if ( sim_param(i).SNR_type(2) ~= 'b' )
error( 'The SNR should be stored as Eb/No' );
end
semilogy( sim_param(i).SNR, sim_state(i).SER, sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(3,:) == 1 ) ).legend, 0 );
xlabel( 'Eb/No in dB' );
ylabel( 'SER' );
hold off;
end
% Plot the FER of coded and outage simulations
if ( sum( sum( sim_types(4:5,:) ) ) )
% First plot FER vs. Eb/No
fig_number = fig_number + 1;
figure( fig_number );
% Outage Probability
for (i=find( sim_types(5,:) == 1 ) )
% If stored as Es/No, convert to Eb/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
else
% This is stored as Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
end
% Plot FER versus Eb/No in dB
figure( fig_number );
semilogy( EbNodB, sim_state(i).FER, sim_param(i).linetype );
hold on;
end
% FER of coded modulation
for (i=find( sim_types(4,:) == 1 ) )
% If stored as Es/No, convert to Eb/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
else
% This is stored as Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
end
% only plot the last iteration
if ( length( sim_param(i).max_iterations ) )
max_iter = sim_param(i).max_iterations;
else
max_iter = 1;
end
% Plot FER versus Eb/No in dB
figure( fig_number );
semilogy( EbNodB, sim_state(i).FER( max_iter, : ), sim_param(i).linetype );
hold on;
end
figure( fig_number );
legend( sim_param( find( sim_types(5,:) == 1 ) ).legend, sim_param( find( sim_types(4,:) == 1 ) ).legend, 0 );
xlabel( 'Eb/No in dB' );
ylabel( 'FER' );
% Now plot the other iterations
for (i=find( sim_types(4,:) == 1 ) )
if ( length( sim_param(i).plot_iterations ) )
% make sure that we get both Es/No and Eb/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
else
% This is stored as Es/No
EsNodB = sim_param(i).SNR;
% Convert to Eb/No
EsNo = 10.^(EsNodB/10);
EbNo = EsNo./sim_param(i).rate;
EbNodB = 10*log10(EbNo);
end
% plot the other iterations
figure( fig_number );
semilogy( EbNodB, sim_state(i).FER(sim_param(i).plot_iterations,:), sim_param(i).linetype );
end
end
figure( fig_number );
hold off;
% plot FER vs. Es/No
fig_number = fig_number + 1;
figure( fig_number );
% Outage Probability
for (i=find( sim_types(5,:) == 1 ) )
% If stored as Eb/No, convert to Es/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
% Convert to Es/No
EbNo = 10.^(EbNodB/10);
EsNo = sim_param(i).rate*EbNo;
EsNodB = 10*log10(EsNo);
else
% This is Es/No
EsNodB = sim_param(i).SNR;
end
% Plot FER versus Es/No in dB
figure( fig_number );
semilogy( EsNodB, sim_state(i).FER, sim_param(i).linetype );
hold on;
end
% FER of coded modulation
for (i=find( sim_types(4,:) == 1 ) )
% If stored as Eb/No, convert to Es/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
% Convert to Es/No
EbNo = 10.^(EbNodB/10);
EsNo = sim_param(i).rate*EbNo;
EsNodB = 10*log10(EsNo);
else
% This is Es/No
EsNodB = sim_param(i).SNR;
end
% only plot the last iteration
if ( length( sim_param(i).max_iterations ) )
max_iter = sim_param(i).max_iterations;
else
max_iter = 1;
end
% Plot FER versus Es/No in dB
figure( fig_number );
semilogy( EsNodB, sim_state(i).FER( max_iter, : ), sim_param(i).linetype );
hold on;
end
figure( fig_number );
legend( sim_param( find( sim_types(5,:) == 1 ) ).legend, sim_param( find( sim_types(4,:) == 1 ) ).legend, 0 );
xlabel( 'Es/No in dB' );
ylabel( 'FER' );
% Now plot the other iterations
for (i=find( sim_types(4,:) == 1 ) )
if ( length( sim_param(i).plot_iterations ) )
% If stored as Eb/No, convert to Es/No
if ( sim_param(i).SNR_type(2) == 'b' )
% This is Eb/No
EbNodB = sim_param(i).SNR;
% Convert to Es/No
EbNo = 10.^(EbNodB/10);
EsNo = sim_param(i).rate*EbNo;
EsNodB = 10*log10(EsNo);
else
% This is Es/No
EsNodB = sim_param(i).SNR;
end
% plot the other iterations
figure( fig_number );
semilogy( EsNodB, sim_state(i).FER(sim_param(i).plot_iterations,:), sim_param(i).linetype );
end
end
figure( fig_number );
hold off;
end
% plot throughput vs. Es/No, if there are any throughput curves requested
if ( sum( sim_types(6,:) ) )
fig_number = fig_number + 1;
figure( fig_number );
% plot throughput vs. Es/No
for (i=find( sim_types(6,:) == 1 ) )
plot( sim_param(i).SNR, sim_state(i).throughput, sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(6,:) == 1 ) ).legend, 2 );
xlabel( 'Es/No in dB' );
ylabel( 'Normalized throughput' );
hold off;
end
% plot min Eb/No vs. h for nonorthogonal FSK under BW constraints.
if ( sum( sim_types(7,:) ) )
fig_number = fig_number + 1;
figure( fig_number );
% plot min Eb/No vs. h
for (i=find( sim_types(7,:) == 1 ) )
[Y,I] = sort( sim_param(i).h );
plot( sim_param(i).h(I), sim_state(i).min_EbNodB(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(7,:) == 1 ) ).legend, 2 );
xlabel( 'h' );
ylabel( 'min Eb/No (in dB)' );
hold off;
fig_number = fig_number + 1;
figure( fig_number );
% plot min Eb/No vs. rate
for (i=find( sim_types(7,:) == 1 ) )
[Y,I] = sort( sim_state(i).best_rate );
plot( sim_state(i).best_rate(I), sim_state(i).min_EbNodB(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(7,:) == 1 ) ).legend, 2 );
xlabel( 'code rate r' );
ylabel( 'min Eb/No (in dB)' );
hold off;
end
% plot min Eb/No vs. B for nonorthogonal FSK under BW constraint B.
if ( sum( sim_types(8,:) ) )
fig_number = fig_number + 1;
figure( fig_number );
% plot min Eb/No vs. B
for (i=find( sim_types(8,:) == 1 ) )
[Y,I] = sort( sim_param(i).bwconstraint );
plot( sim_param(i).bwconstraint(I), sim_state(i).min_EbNodB(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(8,:) == 1 ) ).legend, 2 );
xlabel( 'Bandwidth B' );
ylabel( 'min Eb/No (in dB)' );
hold off;
fig_number = fig_number + 1;
figure( fig_number );
% plot eta vs. min Eb/No
for (i=find( sim_types(8,:) == 1 ) )
[Y,I] = sort( sim_param(i).bwconstraint );
% plot( sim_state(i).min_EbNodB(I), 1./sim_param(i).bwconstraint(I), sim_param(i).linetype );
plot( 1./sim_param(i).bwconstraint(I), sim_state(i).min_EbNodB(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(8,:) == 1 ) ).legend, 2 );
% ylabel( '\eta' );
% xlabel( 'minimum Eb/No in dB' );
xlabel( '\eta in bps/Hz' );
ylabel( 'Minimum Eb/No in dB' );
hold off;
fig_number = fig_number + 1;
figure( fig_number );
% plot optimal h vs. B
for (i=find( sim_types(8,:) == 1 ) )
[Y,I] = sort( sim_param(i).bwconstraint );
plot( sim_param(i).bwconstraint(I), sim_param(i).h(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(8,:) == 1 ) ).legend, 2 );
xlabel( 'Bandwidth B' );
ylabel( 'optimal h' );
hold off;
fig_number = fig_number + 1;
figure( fig_number );
% plot optimal rate vs. B
for (i=find( sim_types(8,:) == 1 ) )
[Y,I] = sort( sim_param(i).bwconstraint );
plot( sim_param(i).bwconstraint(I), sim_state(i).best_rate(I), sim_param(i).linetype );
hold on;
end
legend( sim_param( find( sim_types(8,:) == 1 ) ).legend, 2 );
xlabel( 'Bandwidth B' );
ylabel( 'optimal rate' );
hold off;
end
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