new PropagationLossModel

src/de/tud/kom/p2psim/impl/topology/views/wifi/phy/propagation/loss/LogDistancePropagationLossModel.java

@@ -121,6 +121,10 @@ public class LogDistancePropagationLossModel extends PropagationLossModel {
 		return exponent;
 	}
 
+	protected double getReferenceLoss() {
+		return referenceLoss;
+	}
+
 	/**
 	 * The lamba and the referenceLoss is depending of the frequency and the
 	 * referenceDistance. If one of this values changed, then should be updated

src/de/tud/kom/p2psim/impl/topology/views/wifi/phy/propagation/loss/SurreyPropagationLossModel.java

+package de.tud.kom.p2psim.impl.topology.views.wifi.phy.propagation.loss;
+
+import de.tudarmstadt.maki.simonstrator.api.component.sensor.location.Location;
+
+/**
+ * A model suited for connections between antennas at heights of 0.5-3m. Defined
+ * in:
+ * <p>
+ * Konstantinou, K., Kang, S., & Tzaras, C. (2007). A measurement-based model for
+ * mobile-to-mobile UMTS links. IEEE Vehicular Technology Conference, 529–533.
+ * http://doi.org/10.1109/VETECS.2007.120
+ * <p>
+ * The model defines path loss for line of sight (LOS) and non light of sight (NLOS)
+ * propagation.
+ * <pre>
+ * PLOS = 4.62 + 20 * log10(4π/λ) - 2.24ht - 4.9hr + 29.6 * log10(d)
+ * PNLOS = 20 * log10(4π/λ) - 2 *hr + 40 * log10(d) + C
+ *
+ * C = 0 if dense urban (HB > 18m), -4 else (HB < 12m)
+ * </pre>
+ * <p>
+ * with λ the wavelength, HB average building height, ht and hr the height of
+ * the transmitting and receiving antenna above ground, d the distance.
+ * <p>
+ * The average path loss is estimated as <code>PL = α PLLOS + (1-α)PLNLOS</code>, where
+ * α is the probability that there is a LOS connection between transmitter and
+ * receiver.
+ *
+ * @author Tim Feuerbach
+ */
+public class SurreyPropagationLossModel extends LogDistancePropagationLossModel {
+    private double C = 0;
+    private double alpha = 0.098601797632;
+    private double transmitterHeight = 1.6;
+    private double receiverHeight = 1.6;
+
+    /**
+     * Distance below which the model will always return the TX power.
+     */
+    private double minDistance = 0.5d;
+
+    @Override
+    public double getRxPowerDbm(double txPowerDbm, Location a, Location b) {
+        return getRxPowerDbm(txPowerDbm, a.distanceTo(b));
+    }
+
+    @Override
+    public double getRxPowerDbm(double txPowerDbm, double distance) {
+        if (distance < minDistance) return txPowerDbm;
+        double pLOS = 4.62 + getReferenceLoss() - 2.24 * transmitterHeight - 4.9 * receiverHeight + 29.6 *
+                Math.log10(distance);
+        double pNLOS = getReferenceLoss() - 2 * receiverHeight + 40 * Math.log10(distance) + C;
+        double loss = alpha * pLOS + (1 - alpha) * pNLOS;
+        return txPowerDbm - Math.max(0, loss);
+    }
+
+    @Override
+    public double getDistance(double txPowerDbm, double rxPowerDbm) {
+        double p = Math.abs(rxPowerDbm - txPowerDbm);
+        // TODO use less obscure formulation, this one was obtained from Wolfram Alpha by solving for d
+        return Math.exp((-285379588546205536L * alpha * C - 827600806783996032L * alpha *
+                receiverHeight - 639250278343500416L * alpha * transmitterHeight + 1318453699083469568L
+                * alpha + 285379588546205536L * C - 285379588546205536L * p - 570759177092411072L *
+                receiverHeight + 285379588546205536L * getReferenceLoss()) / (1288963317755749376L *
+                alpha - 4957551222137499648L));
+
+    }
+
+    public void setIsUrban(boolean isUrban) {
+        C = (isUrban) ? 0 : -4;
+    }
+
+    public void setLosProbability(double losProbability) {
+        this.alpha = losProbability;
+    }
+
+    public void setTransmitterHeight(double transmitterHeight) {
+        this.transmitterHeight = transmitterHeight;
+    }
+
+    public void setReceiverHeight(double receiverHeight) {
+        this.receiverHeight = receiverHeight;
+    }
+}