diff --git a/python/examples/simulate_error_rate.py b/python/examples/simulate_error_rate.py
index c71e3ad..e913a21 100644
--- a/python/examples/simulate_error_rate.py
+++ b/python/examples/simulate_error_rate.py
@@ -29,17 +29,14 @@ class SimulationArgs:
 
 
 def decode(tracker, y, H, args: SimulationArgs) -> np.ndarray:
-    x_hat = np.mod(np.round(y), 2).astype('int32')
+    x_hat = np.where(y >= 0, 0, 1)
 
     s = np.concatenate([y, np.array([0])])
     for i in range(args.homotopy_iter):
-        x_hat = np.mod(np.round(s[:-1]), 2).astype('int32')
+        x_hat = np.where(s[:-1] >= 0, 0, 1)
         if not np.any(np.mod(H @ x_hat, 2)):
             return x_hat
 
-        # if s[-1] > 1.5:
-        #     return x_hat
-
         try:
             s = tracker.step(s)
         except:
@@ -67,22 +64,28 @@ def simulate_error_rates_for_SNR(H, Eb_N0, args: SimulationArgs) -> typing.Tuple
     for _ in tqdm(range(args.max_frames)):
         Eb_N0_lin = 10**(Eb_N0 / 10)
         N0 = 1 / (2 * k / n * Eb_N0_lin)
-        y = np.zeros(n) + np.sqrt(N0) * np.random.normal(size=n)
+
+        u = np.random.randint(2, size=k)
+        # u = np.zeros(shape=k).astype(np.int32)
+        c = np.array(GF(u) @ G)
+        x = 1 - 2*c
+
+        y = x + np.sqrt(N0) * np.random.normal(size=n)
 
         homotopy.update_received(y)
 
-        x_hat = decode(tracker, y, H, args)
+        c_hat = decode(tracker, y, H, args)
 
-        if np.any(np.mod(H @ x_hat, 2)):
+        if np.any(np.mod(H @ c_hat, 2)):
             tracker.set_sigma(-1 * args.sigma)
-            x_hat = decode(tracker, y, H, args)
+            c_hat = decode(tracker, y, H, args)
             tracker.set_sigma(args.sigma)
 
-            if np.any(np.mod(H @ x_hat, 2)):
+            if np.any(np.mod(H @ c_hat, 2)):
                 decoding_failures += 1
 
-        bit_errors += np.sum(x_hat != np.zeros(n))
-        frame_errors += np.any(x_hat != np.zeros(n))
+        bit_errors += np.sum(c_hat != c)
+        frame_errors += np.any(c_hat != c)
         num_frames += 1
 
         if frame_errors >= args.target_frame_errors:
@@ -95,7 +98,7 @@ def simulate_error_rates_for_SNR(H, Eb_N0, args: SimulationArgs) -> typing.Tuple
     return FER, BER, DFR, frame_errors
 
 
-def simulate_error_rates(H, Eb_N0_list, args: SimulationArgs) -> typing.Tuple[np.ndarray, np.ndarray, np.ndarray, np.ndarray]:
+def simulate_error_rates(H, Eb_N0_list, args: SimulationArgs) -> pd.DataFrame:
     FERs = []
     BERs = []
     DFRs = []
@@ -106,8 +109,11 @@ def simulate_error_rates(H, Eb_N0_list, args: SimulationArgs) -> typing.Tuple[np
         BERs.append(BER)
         DFRs.append(DFR)
         frame_errors_list.append(num_frames)
+        print(pd.DataFrame({"SNR": Eb_N0_list[:len(FERs)], "FER": FERs, "BER": BERs,
+                            "DFR": DFRs, "frame_errors": frame_errors_list}))
 
-    return np.array(FERs), np.array(BERs), np.array(DFRs), np.array(frame_errors_list)
+    return pd.DataFrame({"SNR": Eb_N0_list, "FER": FERs, "BER": BERs,
+                         "DFR": DFRs, "frame_errors": frame_errors_list})
 
 
 def main():
@@ -157,11 +163,8 @@ def main():
         target_frame_errors=args.target_frame_errors)
 
     SNRs = np.arange(args.snr[0], args.snr[1], args.snr[2])
-    FERs, BERs, DFRs, frame_errors_list = simulate_error_rates(
-        H, SNRs, simulation_args)
+    df = simulate_error_rates(H, SNRs, simulation_args)
 
-    df = pd.DataFrame({"SNR": SNRs, "FER": FERs, "BER": BERs,
-                      "DFR": DFRs, "frame_errors": frame_errors_list})
     print(df)