# Low-Cost _Ka_-Band Satellite Receiver Data Preprocessing for Tropospheric Propagation Studies
## 2 Materials and Methods
### Experimental Setup
#### 2.1.2 The Indoor Unit  
This takes care of a second frequency conversion, signal processing, and data logging. It is composed of an SDR unit (bladeRF x40) [29] connected to a PC. The PC runs under Windows 10 and carries out both signal processing and data logging tasks. The bladeRF SDR is fit with an RF transceiver, which performs a second down-conversion and quadrature sampling (up to 40 Msps outputting 12 bit \(IQ\) samples). In spite of the availability of this large bandwidth, we set the SDR unit to its minimum tunable bandwidth, i.e., 1.5 MHz, to be centered approximately about the beacon frequency, and to a sampling rate of 2 Msps. To avoid unexpected problems, the received beacon signal was moved away from the DC frequency and located somewhere midway between 0 and one-half of \(f_{\mathrm{s}}\) (sampling rate). It is common in affordable SDR hardware to observe a significant DC component at a complex baseband, thus the decision of tuning the beacon away from 0 Hz for measuring its power. Since no further filtering is performed at this point, the baseband presents flat spectral characteristics except for samples very close to the selected spectrum edges. Furthermore, the beacon (19,680 MHz) is situated in a quiet part of the transponder's bandwidth, some 20 MHz away from the limit of the modulated signal spectrum (19,700 MHz). Note also that our measurement bandwidth, as said above, is only 1.5 MHz, which allows achieving the wanted spectral flatness. The closest spot beam center frequency is 19,818.75 MHz [30]. The obtained \(I\) and \(Q\) components are passed to the PC via a USB 3.0 port. Finally, these signals are processed and stored along with the resulting measurements in the PC. Signal processing involving the identification and measurement of the beacon at the baseband is performed. The signal processing is very simple: it involves computing a long Fast Fourier Transform (FFT) of consecutive, non-overlapping signal blocks, identification of the beacon signal at the baseband, and power summing three spectral FFT bins around the beacon signal [31]. A single spectral sample is not enough unless the sample is exactly at the center of the frequency bin. Given the presence of drift, it is simpler to power sum the peak and side frequency bins. We chose an FFT of size \(2^{18}\) points, which together with a sampling rate of 2 MHz yielded a spectral bin size of 7.6294 Hz and also an output data rate by the same amount. Note that this final sampling rate fulfills the [PERSON] criterion for the fastest of the various phenomena involved, i.e., scintillation with negligible spectral components beyond 3 Hz. We chose to measure the power in three adjacent bins, one at each side of that with the spectral maximum. This is equivalent to a measurement bandwidth of \(\approx\)23 Hz. Non-overlapping FFTs were employed in order not to excessively burden the controlling computer so that real-time measurements could be obtained. The resulting information represents the variations in the power level of the received beacon signal, \(S\), plus noise, \(N\). Note that the noise originates both at the receiver (noise factor) and the antenna (antenna noise temperature). Thus, we are actually measuring \(S+N\) instead of only \(S\). With computer simulations assuming Gaussian \(I\) and \(Q\) noise components plus a steady direct signal, we verified that as long as we had over about 10 dB Signal-power-to-Noise-power Ratio (v), we could obtain fairly uncorrupted signal samples. Many setups, e.g., [18; 32], including ours, also perform an additional calculation of the overall power at the baseband (from \(-f_{s}/2\) to \(f_{s}/2\)). The purpose of this is to help identify rain events. This is similar to what radiometers do, albeit with much more stable, constant gain receivers. In our case, we cannot tell an increase in water vapor or the presence of clouds through this calculation, but still, we can obtain a clear indication of the presence of rain events: a decrease in the beacon power is accompanied by an increase in the noise.