# An Assessment of Environmental RF Noise Due to IoT Deployment
## 4 IoT Radio Noise Generation  
Although studies have predicted massive deployment of the IoT industry, at the time of this writing, South African environments are still not populated much with IoT operations at a large scale. It was, therefore, necessary to develop a mechanism for generating RF noise emulating the IoT radio transmissions.  
[PERSON] et al. [1] highlighted the IoT's complex background in data generation. By operational definition, IoT connects every object: human clothing, robots, home appliances, mobile phones, and more. In 2012, it was recorded that about 2.5 quintillion (2.5 \(\times\) 10\({}^{18}\)) pieces of data were produced daily. The IoT data generation differed in speed, scalability, dynamics, and heterogeneity. Concerning the data rate, the challenges were due to handling data generated at high sampling rates, as they require efficient and faster processing.  
Conversely, data generated at low data rates also introduced risks of losing some information. IoT device mobility added complexity because the sensing data would have to operate and reflect its performance at different locations. Product delicacy in some applications, especially when deployed in harsh environments, could affect data generation, as devices may underperform due to failure or intermittent connections. The IoT industry anticipated the creation of various applications with mixed data models and formats [1].  
There are many IoT characteristics to consider in the physical layers, data generation, communication protocols, and operating modes. The understanding in this paper was that it could not be realistic to conceive a unique IoT noise-generating model that satisfied all the requirements.  
In this paper, the IoT noise generator (ING) units transmitted modulated random signals at controllable time intervals called transmit rates. On power up, the modules were idle and could broadcast no signal. When the button was pressed, the microcontroller incremented the transmit rate counter from transmit rate Tx0 to transmit rate Tx10. After Tx10, the counter overflowed and reset to Tx0. As shown in Table 1, the microcontroller set pre-programmed time intervals for individual transmit rates. An LED was programmed to flash according to the transmit rate. With this operating mode, the higher the transmit rate, the more the ING units emit RF signals into free space and the higher the amount of ambient RF activities; therefore, the system could emulate the quantity of radio noise deposited in the environment.  
The design of the ING hardware followed these specifications:  
* Three board variants: 433 MHz, 868 MHz, and 2.4 GHz;
* Microcontroller: Texas Instruments(r) CC1352R;  
\begin{table}
\begin{tabular}{c c} \hline \hline
**Transmit Rate** & **Transmit Interval (Seconds)** \\ \hline Tx0 & Idle \\ Tx1 & 5 \\ Tx2 & 4 \\ Tx3 & 3.5 \\ Tx4 & 3 \\ Tx5 & 2.5 \\ Tx6 & 2 \\ Tx7 & 1.5 \\ Tx8 & 1 \\ Tx9 & 0.5 \\ Tx10 & 0.1 \\ \hline \hline \end{tabular}
\end{table}
Table 1: Transmit rates and corresponding time intervals.  
* RF balun and matching network: discrete components;
* RF front-end: RF-specified capacitors and inductors;
* Printed circuit board (PCB) trace antennas: custom design of three separate models for each frequency;
* Battery-operated: CR2032; 3V;
* Push-button;
* LED signal indicator;
* Low cost;
* Compliance with local regulations on electronic communication [8].  
Figure 3 introduces the functional block diagram of the ING. Figure 4 shows the three PCB variants. Color codes red, green, and black differentiated the 433 MHz, 868 MHz, and 2.4 GHz variants, respectively. Each PCB required a specific on-board trace antenna designed according to the frequency of interest. The experiment included 15 boards on each frequency. The production delivered a total of 45 PCBs.  
Figure 4: Assembled boards of the IoT noise generators.  
Figure 3: Functional schematic of the IoT noise generator hardware.