diff --git a/ofdm/fdet_eval.m b/ofdm/fdet_eval.m
index e3ee03f..280b424 100644
--- a/ofdm/fdet_eval.m
+++ b/ofdm/fdet_eval.m
@@ -1,36 +1,46 @@
-function fdet_eval(f_true, knoise_dB)
+function fdet_eval(f_true, knoise_dB, numFrames)
 
 fs = 48000;
 N = 1024;
-
+K = numFrames;
 phi_true = 1;
 
-x_true = exp(j*(2*pi*f_true/fs*(0:N-1)'+phi_true)) + sqrt(10^(knoise_dB/10))*randn(N,1);
+% Adaption rate
+mu = 20.0;
+
+% Generate signal
+x_true = exp(j*(2*pi*f_true/fs*(0:K*N-1)'+phi_true)) + sqrt(10^(knoise_dB/10))*randn(K*N,1);
 
 % Initial guess
 X = fft(x_true, N);
 [v maxk] = max(abs(X));
-f_est = (maxk-1)*fs/N
-phi_est = angle(x_true(1));
-mu = 1.0;
+f_est = (maxk-1)*fs/N; % * (1+angle(X(maxk)))
 
-for k=1:500
+for k=1:K
+    xp = x_true((k-1)*N+1:k*N);
+    phi_est = angle(xp(1));
     x_est = exp(-j*(2*pi*f_est/fs*(0:N-1)'+phi_est));
-    dmod(k) = sum(x_true.*x_est);
+    dmod(k) = sum(xp.*x_est);
     err(k) = sign(imag(dmod(k)))*(1-real(dmod(k)/abs(dmod(k))))^.5;
     f_est = f_est + mu*err(k);
 	f(k) = f_est;
+    phi(k) = phi_est;
 end;
 
 f_true = f_true
 f_est = f_est
+mean_fest = mean(f(K/2+1:K))
+error_ppm = 1E6*(1-mean_fest/f_true)
 
 close all;
-subplot(3,1,1)
-plot(1:lge(f), 1-real(dmod)./abs(dmod), 1:lge(f), imag(dmod)./abs(dmod)); grid;
+subplot(4,1,1)
+plot(1:lge(f), 1-real(dmod)./abs(dmod), 1:lge(f), imag(dmod)./abs(dmod), 1:lge(f), real(dmod)./abs(dmod)); grid;
 
-subplot(3,1,2)
+subplot(4,1,2)
 plot(1:lge(f), err, '-*'); grid;
 
-subplot(3,1,3)
+subplot(4,1,3)
 plot(1:lge(f), f); grid;
+
+subplot(4,1,4)
+plot(1:lge(f), angle(dmod)); grid;