Info

This question is closed. Reopen it to edit or answer.

Bit Error Rate High Values

2 views (last 30 days)
Kawther
Kawther on 1 Dec 2014
Closed: MATLAB Answer Bot on 20 Aug 2021
Dear All,
I am using this code to find the bit error rate for the Kmeans clustering algorithm for receving a QPSK modulated data. Running the code high BER values are obtained (something more than 80). Can anyone help me with that ASAP.
clear all
clc
T=[ 2+2*i 2-2*i -2+2*i -2-2*i];
A=randn(150,2)+2*ones(150,2); C=randn(150,2)-2*ones(150,2);
B=randn(150,2)+2*ones(150,2); F=randn(150,2)-2*ones(150,2);
D=randn(150,2)+2*ones(150,2); G=randn(150,2)-2*ones(150,2);
E=randn(150,2)+2*ones(150,2); H=randn(150,2)-2*ones(150,2);
X = [A; B; D; C; F; E; G; H];
for k=1:5
[idx, centroids] = kmeans(X, k, 'Replicates', 20);
x = X(:,1);
y = X(:,2);
BER=[];
for nn=1:4
ber=0;
gt = zeros(1,4);
for idx = 1 : 4
[dummy,gt(idx)] = min(sum(bsxfun(@minus, [real(T(idx)), imag(T(idx))],...
centroids).^2, 2));
end
randn('seed',123);
rand_ind = randi(4, 10, 1);
test_sequence = T(rand_ind);
gt_labels = gt(rand_ind);
x = real(test_sequence).*(nn*randn(1, 10));
y = imag(test_sequence).*(nn*randn(1, 10));
labels = zeros(1, 10);
for idx = 1 : 10
[dummy,labels(idx)] = min(sum(bsxfun(@minus, [x(idx), y(idx)],...
centroids).^2, 2));
end
ber = sum(labels ~= gt_labels) / 10 * 100;
BER=[BER ber];
end
plot(nn,BER)
end
Thank you very much. Kawther

Answers (0)

This question is closed.

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!