diff --git a/ofdm/fdet_eval.m b/ofdm/fdet_eval.m
index 4124cf8..d67490e 100644
--- a/ofdm/fdet_eval.m
+++ b/ofdm/fdet_eval.m
@@ -4,40 +4,36 @@ function fdet_eval(f_true, phi_true, knoise_dB, p)
 
 fs = 48000;
 N = 1024;
-K = 20;
+K = 40;
 
 f_min = p(1);
 f_max = p(2);
 f_step = p(3);
 
-% Adaption rate
-mu = 0.01;
-
 % 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);
 
-last_mag = 0;
-
 % Initial guess
-f_est = fdet_coarse(x_true, N, fs, f_min, f_step, f_max)
+f_coarse = fdet_coarse(x_true, N, fs, f_min, f_step, f_max)
 
-Xm = zeros(N, 1);
+phi_est = 0;
+f_est = f_coarse;
 for k=1:K
-    xp = x_true((k-1)*N+1:k*N);
-    x_est = exp(-j*(2*pi*f_est/fs*(0:N-1)' + 0));
-    dmod(k) = sum(xp.*x_est);
-    mag = abs(dmod(k))/N;
-    err(k) = mag-last_mag;
-    err(k) = sin(1*err(k));
-    last_mag = mag;
-    phi(k) = angle(dmod(k));
-    f_est = f_est + mu*err(k);
 	f(k) = f_est;
+    xp = x_true((k-1)*N+1:k*N);
+    x_est = exp(-j*(2*pi*f_est/fs*(0:N-1)' + phi_est));
+    dmod(k) = sum(xp.*x_est);
+    f_f = angle(dmod(k))/N*fs/(2*pi);
+    err(k) = f_f;
+    f_est = f_est + f_f;
+    dphi_est = 2*pi*mod(f_est/fs*N, 1);
+    phi_est = phi_est + dphi_est;
 end;
 
 f_est = f_est
-mean_fest = mean(f(K/2+1:K))
-error_ppm = 1E6*(1-mean_fest/f_true)
+
+error_ppm = 1E6*(1-f_est/f_true)
+
 
 close all;
 subplot(4,1,1)
@@ -50,5 +46,5 @@ subplot(4,1,3)
 plot(1:lge(f), f); grid; legend('f');
 
 subplot(4,1,4)
-plot(1:lge(f), phi, '-*'); grid; legend('phi');
+plot(1:lge(f), angle(dmod), '-*', 1:lge(f), diff(angle([0 dmod])), 'r-*'); grid; legend('phi', 'dphi');