diff --git a/where_fi/config/models.py b/where_fi/config/models.py
index 9d07d90..8033205 100644
--- a/where_fi/config/models.py
+++ b/where_fi/config/models.py
@@ -105,16 +105,16 @@ class Config(BaseModel):
         raise ValueError(f"{self.central_freq} is not a valid Wi-Fi channel")
 
     @property
-    def num_pilots(self) -> int:
+    def num_guards(self) -> int:
         if self.channel_width == 20:
-            return 8
-        if self.channel_width == 40:
-            return 14
-        return 24
+            return 7
+        return 11
 
     @property
     def subcarriers(self) -> int:
-        return int((self.channel_width * 1e6) // self.delta_f) - self.num_pilots
+        return (
+            int((self.channel_width * 1e6) // self.delta_f) - self.num_guards
+        ) // self.preprocessing.subcarrier_step
 
     @property
     def _delta_f_no_skipping(self) -> int:
diff --git a/where_fi/processing/preprocess.py b/where_fi/processing/preprocess.py
index b933192..be37609 100644
--- a/where_fi/processing/preprocess.py
+++ b/where_fi/processing/preprocess.py
@@ -147,11 +147,27 @@ class Preprocessor:
 
         This is done by averaging the subcarriers before and after the pilot
         subcarriers. Pilots are detected by checking that the value is exactly 0.
+
+        Also, it adds placeholders for the middle null subcarriers.
         """
+
+        num_middle = 1 if config.channel_width == 20 else 3
+        assert csi.shape[0] + num_middle == config.subcarriers
+        with_middle = np.zeros(
+            (csi.shape[0] + num_middle, csi.shape[1], csi.shape[2]), dtype=np.complex64
+        )
+        with_middle[: csi.shape[0] // 2, :, :] = csi[: csi.shape[0] // 2, :, :]
+        with_middle[csi.shape[0] // 2 + num_middle :, :, :] = csi[
+            csi.shape[0] // 2 :, :, :
+        ]
+        if num_middle == 3:
+            with_middle[csi.shape[0] // 2 + 1, :, :] = (
+                csi[csi.shape[0] // 2 - 1, :, :] + csi[csi.shape[0] // 2, :, :]
+            ) / 2
         return np.where(
-            np.expand_dims(csi[:, 0, 0] == 0, axis=(1, 2)),
-            correlate(csi, [[[1 / 2]], [[0]], [[1 / 2]]], mode="same"),
-            csi,
+            np.expand_dims(with_middle[:, 0, 0] == 0, axis=(1, 2)),
+            correlate(with_middle, [[[1 / 2]], [[0]], [[1 / 2]]], mode="same"),
+            with_middle,
         )
 
     def bandpass(self, csi: CSIMatrix) -> CSIMatrix:
@@ -206,7 +222,7 @@ class Preprocessor:
                 case "bandpass":
                     h_hat = self.bandpass(h_hat)
 
-        logger.debug(f"CSI shape: {h_hat.shape}")
+        logger.info(f"CSI shape: {h_hat.shape}")
 
         self._last_sample = h_hat