**2.2 Data processing**

*Wireless Sensor Networks - Design, Deployment and Applications*

**Parameter Value**

S1 One interferer #1 S2 Two interferers #1 and #3 S3 Three interferers #1, #2, and #3 S4 Four interferers (farthest position) #1, #2, #3, and #4 S5 Four interferers (middle position) #1, #2, #3, and #4 S6 Four interferers (closest position) #1, #2, #3, and #4

Transmission power −3 dBm

Center frequency 868 MHz (LoRa)/2.484 GHz (Wi-Fi) Bandwidth 125 kHz (LoRa)/5 MHz (Wi-Fi) Antenna gain 2 dBi (LoRa)/4 dBi (Wi-Fi)

**Scenario description Active transmitters**

The APS collects the measurement samples by moving along the [6000 x 2000] mm plane for each of the four heights with a step of 1000 mm in the x-coordinate (i.e., the length) and 200 mm in the y-coordinate (width), as underlined in **Figure 3**. As a result, each plane contains 77 measuring points (marked with ×). At each point, the APS performs one measurement over a period of 7 s. After covering all points of the current plane, the APT is elevated by 250 mm and the process is repeated for each of the four heights (0, 250, 500, and 750 mm in

**228**

**Table 2.**

**Table 1.**

*Deployment scenarios.*

**Figure 2.** *APS and APT.*

*Operational parameters.*

the z-coordinate).

To construct the 3D interference maps, the measured signal batches at each measurement point need to be filtered out so that only the samples with the strongest amplitude remain. Thus, their mean which characterizes the signal strength at this point will be maximized. The filtering is performed on the basis of energy detection spectrum sensing in the following way. For each 256 samples in the signal batch, their mean is compared against a constant decision threshold that is predetermined based on the highest instantaneous amplitude shown in the time domain representation of the batch. The higher the threshold's value is, the fewer samples will be produced in the resulting signal after the filtration. A minimal number of samples is chosen (at least a few hundred, usually in CR studies, over a few thousand [25], 30,000 in this case). If the threshold is too high for at least that number of samples to be produced, it is lowered by 2.5%. This coefficient is determined empirically as a viable compromise between the resulting number of samples and the speed of the process (a smaller reduction decreases the speed but will lead to limiting the signal samples to those which will amount to the highest mean).

#### **3. 3D interference maps**

The mean value of the filtered signal determines the power of the received interference power at each measurement point. In each of the six scenarios, a 3D interference map is constructed for both the Wi-Fi and LoRa standards via cubic interpolation of the received interference power means of the 77 measurement points at each of the four elevation levels (0, 250, 500, and 750 mm) in a separate plane. These planes describe the 2D interference distributions (illustrated with the color map) at each height, while together they represent the interference in 3D.

The interference maps for LoRa and Wi-Fi for the six scenarios are illustrated in **Figures 4**–**13**. To examine more closely some sections of the maps' layers which are partly obstructed by higher planes (i.e., the *y*-coordinate interval of [0; 1000] mm), they are represented as 3D bar plots. Such graphics are included for Scenarios **S1** and **S6** for LoRa (**Figures 5** and **8**) and **S3** and **S5** for Wi-Fi (**Figures 11** and **13**)

#### **Figure 4.**

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S1** *(one active transmitter).*

**Figure 5.** *3D bar plot for the LoRa sensor, z = [0, 250, 500, 750] and x = [−2000, −0, 2000], Scenario* **S1***.*

because they provide significant information for weak-signal spots which are not clearly seen in the complete 3D interference maps. **Table 3** outlines the coordinates (in *x*- and *y*-axes) at which the signal power bars are shown.

Starting with the first four scenarios, the spectrum occupancy is examined with the increase of the number of transmitters. For LoRa, it is clear that a significant portion of the area is permeated with strong signals even for a single active interferer. There is, however, some dissipation with height which creates sections with low interference power (spectrum holes) where communication may be feasible, especially on the opposite end of the area as seen from **Figure 5**. They are also present, even though much more limited, for the second scenario (**Figure 6**) and are localized away from the active interferers (#1 and #3, situated on bottom-right and top-left corners of **Figure 1**, respectively). As the number of emitters is increased, sections with very high interference power are only broadened (**Figures 7** and **9**).

For the other two scenarios which bring the four active interferers closer to each other (**Figures 10** and **12**), no significant difference in the power intensity is observed. Nevertheless, the sections with the highest interference concentration

**231**

**Figure 6.**

**Figure 7.**

**S3** *(three active transmitters).*

**S2** *(two active transmitters).*

*Interference Mapping in 3D for High-Density Indoor IoT Deployments*

shift from the table's center to the sides. The only spectrum holes are present in the center of Scenario **S6** (**Figures 12** and **13**) at height z = 0 mm. However, they are very limited by the surrounding interference regions and are thus, hardly viable for

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

The same scenarios are illustrated for the Wi-Fi standard (**Figures 4**–**12**). They present more interesting results due to the higher carrier frequency, compared to LoRa. The strongest interference power is generally measured close to the transmitter, nevertheless, this does not hold for every scenario as is seen in **Figures 7** and **9**. Additionally, it is observed that the interfering signals dissipate more intensively in the higher elevation levels (500 and 750 mm) so that the sections with the highest power are shrinking while the medium (yellow/light green) and low (dark green/ violet) regions are expanding (**Figure 8**). Thus, the increase in fading with distance both on the same plane but also with height in 3D is a significant factor in the 2.4 GHz ISM band. The interference sources' influence can be substantially diminished if their height is varied. As a consequence, drone-based and other mobile IoT

the placement of communication nodes.

devices can benefit from their abilities for repositioning in 3D.

*DOI: http://dx.doi.org/10.5772/intechopen.93581*

*Interference Mapping in 3D for High-Density Indoor IoT Deployments DOI: http://dx.doi.org/10.5772/intechopen.93581*

#### **Figure 6.**

*Wireless Sensor Networks - Design, Deployment and Applications*

*3D bar plot for the LoRa sensor, z = [0, 250, 500, 750] and x = [−2000, −0, 2000], Scenario* **S1***.*

(in *x*- and *y*-axes) at which the signal power bars are shown.

because they provide significant information for weak-signal spots which are not clearly seen in the complete 3D interference maps. **Table 3** outlines the coordinates

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

Starting with the first four scenarios, the spectrum occupancy is examined with the increase of the number of transmitters. For LoRa, it is clear that a significant portion of the area is permeated with strong signals even for a single active interferer. There is, however, some dissipation with height which creates sections with low interference power (spectrum holes) where communication may be feasible, especially on the opposite end of the area as seen from **Figure 5**. They are also present, even though much more limited, for the second scenario (**Figure 6**) and are localized away from the active interferers (#1 and #3, situated on bottom-right and top-left corners of **Figure 1**, respectively). As the number of emitters is increased, sections with very high interference power are only broadened (**Figures 7** and **9**). For the other two scenarios which bring the four active interferers closer to each other (**Figures 10** and **12**), no significant difference in the power intensity is observed. Nevertheless, the sections with the highest interference concentration

**230**

**Figure 5.**

**Figure 4.**

**S1** *(one active transmitter).*

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S2** *(two active transmitters).*

#### **Figure 7.**

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S3** *(three active transmitters).*

shift from the table's center to the sides. The only spectrum holes are present in the center of Scenario **S6** (**Figures 12** and **13**) at height z = 0 mm. However, they are very limited by the surrounding interference regions and are thus, hardly viable for the placement of communication nodes.

The same scenarios are illustrated for the Wi-Fi standard (**Figures 4**–**12**). They present more interesting results due to the higher carrier frequency, compared to LoRa. The strongest interference power is generally measured close to the transmitter, nevertheless, this does not hold for every scenario as is seen in **Figures 7** and **9**. Additionally, it is observed that the interfering signals dissipate more intensively in the higher elevation levels (500 and 750 mm) so that the sections with the highest power are shrinking while the medium (yellow/light green) and low (dark green/ violet) regions are expanding (**Figure 8**). Thus, the increase in fading with distance both on the same plane but also with height in 3D is a significant factor in the 2.4 GHz ISM band. The interference sources' influence can be substantially diminished if their height is varied. As a consequence, drone-based and other mobile IoT devices can benefit from their abilities for repositioning in 3D.

#### **Figure 8.**

*3D bar plot for the Wi-Fi sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S3***.*

**Figure 9.**

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S4** *(four active transmitters, farthest position).*

#### **Figure 10.**

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S5** *(four active transmitters, middle position).*

**233**

**Figure 13.**

**Figure 11.**

**Figure 12.**

**S6** *(four active transmitters, closest position).*

*Interference Mapping in 3D for High-Density Indoor IoT Deployments*

*3D bar plot for the Wi-Fi sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S5***.*

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

*3D bar plot for the LoRa sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S6***.*

*DOI: http://dx.doi.org/10.5772/intechopen.93581*

*Interference Mapping in 3D for High-Density Indoor IoT Deployments DOI: http://dx.doi.org/10.5772/intechopen.93581*

#### **Figure 11.**

*Wireless Sensor Networks - Design, Deployment and Applications*

*3D bar plot for the Wi-Fi sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S3***.*

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario* 

**232**

**Figure 10.**

**Figure 8.**

**Figure 9.**

**S4** *(four active transmitters, farthest position).*

**S5** *(four active transmitters, middle position).*

*3D bar plot for the Wi-Fi sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S5***.*

#### **Figure 12.**

*3D interference map for (a) 868 MHz (LoRa) and (b) 2.484 GHz (Wi-Fi) for z = [0, 250, 500, 750], scenario*  **S6** *(four active transmitters, closest position).*

#### **Figure 13.**

*3D bar plot for the LoRa sensor standard, z = [0, 250, 500, 750] and x = [−2800, −1000, 1000, 2800], scenario* **S6***.*


**Table 3.**

*Coordinates in x- and y-axes.*

When it comes to scenarios **S5** and **S6**, there is some noticeable change in the interference distribution (**Figures 10**–**12**), as the spectrum holes shift to the table's center. At the same time, the interference power has increased substantially, mainly in the observed area's periphery. Thus, when the interferers are within a very short distance between each other, it is much more difficult to diminish their influence, even in the higher levels of elevation.
