Problem 13.9
clear all;
close all;
clc;
b = [1, 1,-0.8,-0.3,1,1]; % define channel
m=1000;
% binary source length
s=sign(randn(1,m);
% binary source of length m
r=filter(b,1,s); % output of channel
er
Problem 12.1
a)
Decreasing the step size slow the Rate of convergence of the algorithm.
Mu=0.01
Mu=0.1
Increasing the step size will improve the convergence rate but would result in inaccurate results
Problem. 1
We can use other pulse shapes as well. For example, sinusoidal waves and sinc wave etc.
Sine shaped pulse.
This gives us smaller bandwidth. Hence, its possible to get narrow bandwidth pulse
Problem 12.3
Initial Time off set =-1
Eye opens near 1000 iterations. It opens at its widest between 1400-1450 iterations. Convergent value is
approximately 1.
Initial Time offset=-0.5, offset estimat
Problem 11.5
% eyediag.m plot eye diagrams for pulse shape ps
N=1000; m=pam(N,6,12);
% random signal of length N
M=20; mup=zeros(1,N*M);
% oversampling factor of M
mup(1:M:N*M)=m;
% oversample by M
ps
Problem 5.6
Phi=0
Phi= -pi
Phi= -pi/2
Phi= -pi/3
Phi= -pi/6
Phi= pi/6
Phi=pi/3
Pi/2
Phi=pi
Depending on the phase the recovered messages spectrum may be entirely different from that of the
transmitted