# Coverage Extension for the UK Smart Meter Implementation Programme Using Mesh Connectivity
## 3 Results and Discussion  
We made a significant number of measurements in Newbury. The aim here was to evaluate the propagation measurements based on normal performance metrics for error: minimum, maximum, mean, standard deviation, and count. Because of the absence of actual in-premise data and un-observed locations, we made measurements on the streets outside houses across Newbury as shown in Figure 4. This area was chosen to test each of the methodologies against baseline measurements. That way, the measurement points could be excluded from those that would be used to calculate coverage at that location; this exclusion distance was set to 10 m. We needed to include enough sample points to ensure a statistically significant result for prediction; however, with over 17,000 sample points, this was not a problem. Shown below is a subset of the results, representative of the complete set of data obtained through these measurements. From Figures 5-7, the first failure point occurs at \(-101.29\) dBm, which reflects the manufacturer's specification of \(-102\) dBm quite well. Figure 4: Coverage map of where the measurements were made in Newbury. Figure 3: Map of the Greenham Common Airbase test area. (Source: Google Earth Maps). It can be seen from the results in Table 1 that simple slope intercept models perform well. However, there are some strange distance artefacts that are close to Base Station (likely to be GPS issues) and some signal level artefacts limiting the distance (likely related to fast fading). \begin{table}
\begin{tabular}{l l l l l l} \hline \hline
**Model** & **Min Error** & **Max Error** & **Mean Error** & **Std** & **Count** \\ \hline
30 log (d/m) & \(-\)23.77 dB & +33.29 dB & 1.42 dB & 11.05 dB & 1708 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Performance of the 868 MHz prediction models. Figure 5: CDF and PDF based on a simple slope intercept model. Figure 6: The log of the distance versus the log of the signal graph with a simple slope intercept model. Processing this model through a limited set of measurement results, based on GPS and low signal artefacts, provides the results shown in Table 1. This allows planning of mesh networks with reasonable accuracy. Mesh networks will make up a small but important percentage of the overall SM coverage. These homes form small clusters which we decided to call constellations, as they resemble constellations of stars; understanding how data messages will flow through these constellations is vital if we are going to deliver high-performing mesh networks for the Smart Meter Implementation Programme. Furthermore, mesh networks will be used to augment coverage in three ways. We have estimated that the 868 MHz mesh radio system will be required at less than 1% (195,000) of all UK premises, amounting to approximately 28 million homes. However, to support that, we need to deploy enough units with mesh connectivity in cellular coverage to support the mesh-only areas. In summary, we have estimated that there will be three types of mesh deployments (example provided in Figure 8):  
* Ad-hoc Mesh (0.5%): \"Install and leave\", where a cellular + mesh hub has been installed as cellular only cannot connect. This is shown as the yellow locations in the blue coverage area. Additional adjacent premise is automatically identified for cellular + mesh hub installation prior to any installation. * Boundary Mesh (4%): installed to provide a cellular gateway for a mesh area. This is shown as the red locations adjacent to the white no coverage areas, and will include antennas. * Planned Mesh (0.5%): where the property doesn't receive adequate cellular coverage. This is shown as the yellow location in the white no coverage area. Installations did not start until late 2019, but this allowed adequate testing of the mesh wide area solution. The ZigBee radio measurements showed that even at low power, the signals propagate up to 1 km outdoors line-of-sight and still provide service.