Эротические рассказы

Dynamic Spectrum Access Decisions. George F. ElmasryЧитать онлайн книгу.

Dynamic Spectrum Access Decisions - George F. Elmasry


Скачать книгу
and the spectrum sensor performing energy detection need to carry similar steps to calculate the received signal energy. Chapter 3 covers how to use same‐channel in‐band sensing to hypothesize the presence of an interfering signal. This section is intended to show how to piggyback on the communications receiver's energy calculation to create same‐channel in‐band energy sensing.

Schematic illustration of the leveraging signal receiver reconstruction of the received signal for same-channel in-band spectrum sensing.

      While energy detection is a natural outcome of signal decoding, building specialized hardware for spectrum sensing can perform energy detection in different ways. This specialized hardware, which is sometimes referred to as an augmented sensor, may or may not have prior knowledge of the signal bases. The following subsections show different methods that can be utilized by the augmented sensors to perform energy detection.

      2.3.2 Time Domain Energy Detection

Schematic illustration of the time domain energy detection.

      Notice the importance of T in the integrator in Figure 2.5. A signal with weak power spectral density such as a spread spectrum signal would needs a longer time period T. With augmented sensors, the bandpass filter has a critical transfer function that can be expressed as follows:

      In time domain spectrum sensing, the time duration that the sensed signal remaining in a particular state can affect the outcome of the spectrum sensor. This time duration is referred to as the dwell time. The spectrum sensor observation time length should correlate to dwell time. Chapter 3 shows that one advantage of same‐channel in‐band sensing is that the in‐band signal is sensed during a known state and the sensing technique does not observe the signal during multiple states within a single sensing window. That is, the sensing technique can have knowledge of whether the transmitted signal is present or not during the entire sensing window. On the other hand, augmented sensors using time domain energy detection, where the sensed signal may change state during the observation time, can lend a higher probability of false alarm.

      2.3.3 Frequency Domain Energy Detection

Schematic illustration of the 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


Скачать книгу
Яндекс.Метрика