Читать книгу Dynamic Spectrum Access Decisions - George F. Elmasry - Страница 31

With this energy detection technique, the sensor also has to be configured for a center frequency f₀ and a bandwidth W to define the frequency range to sense. The sensor uses a bandpass filter, as with time domain energy detection, followed by an analog‐to‐digital convertor (ADC) to digitize the signal and FFT to convert the signal to the frequency domain (Figure 2.6). The squaring device calculates the energy per each frequency coefficient and the mean value stage is used to calculate the average energy over the observed frequency band.

Figure 2.6 Frequency domain energy detection.

As with time domain energy detection, frequency domain energy detection has to consider the presence of noise. The method used to estimate the noise power spectral density can rely on discrete Fourier transformation (DFT) where the digitized data is divided into segments and a sliding window is used to estimate the average noise spectral density. One reason to choose frequency domain energy detection over time domain energy detection in augmented sensors is the higher accuracy of noise estimation but the price for that is the need for more computational power.

Notice how with the three energy detection techniques covered so far, the outcome is simple:

1 Signal energy level at the defined carrier frequency f0 and bandwidth W, and

2 Noise floor energy at the same carrier and bandwidth.

It is important to note that the hypothesizing and decision‐making processes covered in Chapter 3 can be tricky under certain circumstances, such as fading channels. While frequency domain energy detection can implement good techniques such as the sliding window explained above, distributed and centralized DSA techniques can have a view of spectrum sensing that is more comprehensive than a local node. Distributed and centralized DSA techniques can analyze spectrum sensing information per RF neighbor and further overcome the uncertainty that can result from fading channels.

While Section 2.3.1 introduced same‐channel in‐band sensing, Sections 2.3.2 and 3.3.3 introduced the most common forms of augmented sensing where the augmented sensor can be configured to sense a frequency band defined by the carrier frequency f₀ and bandwidth W as illustrated in Figures 2.4 and 2.5. Augmented sensors can be built to sense a wide band of frequencies and sense multiple sub‐bands each defined by a carrier frequency f₀ and a bandwidth W simultaneously. This simultaneous sensing utilizes parallel paths where each path starts with a bandpass filter configured for the carrier frequency f₀ and bandwidth W for one of sub‐bands being sensed.