%%%%%%%%%%%%%%%%%%%%%% Mean Rate 1 %%%%%%%%%%%%%%%%%%%%%%%%%
%%%%%  Assumptions: 
%%%%%  --- Linear Time Scales: tau_k=tau_1+deltatau (k-1)
%%%%%  --- average symbol time T_n=\tau_1(2+(alpha-1)(n-1))/2
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%

clear all
D=20; % number of discrete points for curve resolution 
ainit=1.2;aend=5;ainc=(aend-ainit)/D;  % Range, and increament of parameter alpha
alpha=ainit:ainc:aend;  % discrete points for curve resolution 
%s=a-1; % s=deltatau/tau_1
R_n=[]; % mean rate
tau_1=1;% Normalization. Value is not need for simulation. 
N=5; % number of channels included for comparison
figure(101)
hold off
for n=2:1:N
    % plot(alpha, 2*log(n)./(2+(alpha-1).*(n-1))/log(2),'linewidth',n-1) % 
    plot(alpha, log(2*log(n)./(2+(alpha-1).*(n-1))/log(2))/log(2),'linewidth',n-1) % log_2 plot of the dependent variable
    hold on
    %R_n=[R_n;2*log(n)./(2+(alpha-1).*(n-1))];
end
legend('n = 2','n = 3','n = 4','n = 5')
%axis([ainit aend min([Ceven(12/2,:) Ceven(4/2,:) Ceven(6/2,:) Ceven(8/2,:)]) max([Ceven(2/2,:) Ceven(4/2,:) Ceven(6/2,:) Ceven(8/2,:)])])
xlabel('\alpha = \tau_{2} / \tau_{2}','fontsize',18)
ylabel('lg(\tau_1R_{n})','fontsize',18)
grid on
