diff --git a/where_fi/application.py b/where_fi/application.py
index d51400a..d0e82bd 100644
--- a/where_fi/application.py
+++ b/where_fi/application.py
@@ -131,7 +131,6 @@ class CSIApplication:
         """
 
         def decorator(data: CSIMatrix) -> None:
-            self.visualise_data(data, visualise.figures.Figure.RAW_CSI)
             func(data)
 
         self.preprocessed_csi_callback = decorator
diff --git a/where_fi/processing/preprocess.py b/where_fi/processing/preprocess.py
index 4f4c70a..8c70b72 100644
--- a/where_fi/processing/preprocess.py
+++ b/where_fi/processing/preprocess.py
@@ -123,9 +123,28 @@ class Preprocessor:
 
         return csi
 
+    def normalise_magnitude(
+        self, csi: CSIMatrix, frames: dict[CSIHost, CSI]
+    ) -> CSIMatrix:
+        """
+        Normalise the magnitude of the CSI data to compensate for the effect of the
+        Automatic Gain Control (AGC) of the receiver
+
+        References:
+        [1] -
+        """
+        rssi = [
+            frames[host].header.rssi1 if antenna == 0 else frames[host].header.rssi2
+            for host, antenna in config.antennas.order
+        ]
+        rssi_linear = np.reshape(10 ** (np.array(rssi) / 10), (1, -1, 1))
+        csi_power = np.sum(np.abs(csi) ** 2)
+        return csi * np.sqrt(rssi_linear / csi_power)
+
     def preprocess(
         self,
         h: CSIMatrix,
+        frames: dict[CSIHost, CSI],
         visualiser: None
         | Callable[[npt.NDArray[Any], visualise.figures.Figure], None] = None,
     ) -> CSIMatrix:
@@ -144,6 +163,7 @@ class Preprocessor:
         # h_hat = correlate(h_hat, np.ones((3, 1, 1)) / 3)
         # h_hat = correlate(h_hat, [[[1 / 4]], [[1 / 2]], [[1 / 4]]], mode="valid")
 
+        h_hat = self.normalise_magnitude(h_hat, frames)
         h_hat = self.remove_sfo(h_hat, visualiser=visualiser)
 
         # Skip subcarrierss per config