Add standardization results

* Add link to retrieve standardization data
* Set standardization values for pattern A-N
* Adapt MIN_OCCURENCES_FACTOR from 0.5% to 5%
* Set scripts/visualize standardize rnti to 11852
* According to std.htc_one recording

README.md

@@ -62,3 +62,7 @@ sudo sysctl -w net.ipv6.conf.lo.disable_ipv6=1
 ```
 
 The configuration can be made persistently by editing/adding `/etc/sysctl.d/`.
+
+## Data
+
+Example data and results can be found [here](https://nextcloud.schmidt-systems.eu/s/AYqZDwtWxAeQY8N).

scripts/visualize_rnti_matching.py

@@ -31,7 +31,7 @@
 MAX_TOTAL_UL_FACTOR = 200.0
 MIN_TOTAL_UL_FACTOR = 0.005 # x% of the expected UL traffic
 MAX_UL_PER_DCI_THRESHOLD = 5_000_000
-MIN_OCCURENCES_FACTOR = 0.005
+MIN_OCCURENCES_FACTOR = 0.05
 
 # Plotting
 PLOT_SCATTER_MARKER_SIZE = 10
@@ -464,7 +464,7 @@ def standardize(settings):
     std_count = (np.mean(count_vec), np.std(count_vec))
     std_total_ul = (np.mean(total_ul_vec), np.std(total_ul_vec))
 
-    std_ul_timeline_median = (
+    ul_timeline_median = (
             np.mean(ul_timeline_matrix[:, 0]),
             np.std(ul_timeline_matrix[:, 0])
     )
@@ -498,7 +498,7 @@ def standardize(settings):
     print("vec![")
     print(f"    ({std_count[0]:.3f}, {std_count[1]:.3f}),")
     print(f"    ({std_total_ul[0]:.3f}, {std_total_ul[1]:.3f}),")
-    print(f"    ({std_ul_timeline_median[0]:.3f}, {std_ul_timeline_median[1]:.3f}),")
+    print(f"    ({ul_timeline_median[0]:.3f}, {ul_timeline_median[1]:.3f}),")
     print(f"    ({ul_timeline_mean[0]:.3f}, {ul_timeline_mean[1]:.3f}),")
     print(f"    ({ul_timeline_variance[0]:.3f}, {ul_timeline_variance[1]:.3f}),")
     print(f"    ({dci_time_deltas_median[0]:.3f}, {dci_time_deltas_median[1]:.3f}),")
@@ -522,7 +522,7 @@ def read_all_recordings(settings):
 
 
 def determine_highest_count_ul_timeline(df):
-    rnti = "11223"
+    rnti = "11852"
     target_traffic: pd.DataFrame = pd.DataFrame()
 
     if not rnti in df.columns:

src/logic/rnti_matcher.rs

@@ -41,7 +41,7 @@ pub const COLLECT_DCI_MAX_TIMESTAMP_DELTA_US: u64 = 50000;
 pub const BASIC_FILTER_MAX_TOTAL_UL_FACTOR: f64 = 200.0;
 pub const BASIC_FILTER_MIN_TOTAL_UL_FACTOR: f64 = 0.005;
 pub const BASIC_FILTER_MAX_UL_PER_DCI: u64 = 5_000_000;
-pub const BASIC_FILTER_MIN_OCCURENCES_FACTOR: f64 = 0.005;
+pub const BASIC_FILTER_MIN_OCCURENCES_FACTOR: f64 = 0.05;
 
 pub const RNTI_RING_BUFFER_SIZE: usize = 5;
 
@@ -805,7 +805,7 @@ fn feature_distance_matrices(
                 &weightings_vector);
 
             // Uncomment and implement debug print if needed
-            // print_debug(&format!("DEBUG [rntimatcher] distances: {:.2}", euclidean_distances));
+            print_debug(&format!("DEBUG [rntimatcher] distances: {:.2}", euclidean_distances));
 
             let mut rnti_and_distance: Vec<(u16, f64)> = cell_traffic.traffic.keys()
                 .cloned()