Page 252 - From Smart Grid to Internet of Energy

224 From smart grid to internet of energy

FIG. 6.10 Classifying of spectrum sensing methods.

The SS methods can be classified into two groups as non-cooperative (or
transmitter detection) and cooperative detection as can be shown in
Fig. 6.10. The non-cooperative methods are depending on the detection of trans-
mitted signal from a PU via local observations of SUs. In this detection
approach, it is assumed that the CR device does not know the location of the
PU. Hence, the SUs should only depend on the detection of poor PU signals
and exploit merely local observations to accomplish the SS process. A CR
device does not possess full information regarding occupied spectrums in the
coverage area. Therefore, there is no possibility to full prevent interference with
the PUs. There are three popular detection approaches for non-cooperative
detection method, which are referred as energy detection, matched filter detec-
tion, and cyclostationary feature detection.
An excellent line of sight (LOS) may be available between PU receiver and
SU. However, the SU may not detect the PU due to shadowing problem that is a
challenging problem for both urban and indoor environments. This issue is called
as hidden terminal problem and cooperative detection methods aims to handle
this problem. Cooperative detection can be divided into two categories as central-
ized and distributed approach. In former approach, a central unit gathers informa-
tion from the CR devices; it determines the possible spectrum bands and shares
this information with other CR devices. In latter approach, central node usage is
not available, and CR devices similarly share sensing data with other CR devices.
While the distributed approach is easily implementable and there is no backbone
infrastructure requirements, the other approach provides more accuracy and can
efficiently diminish shadowing and multi-path fading effects.

6.4.1 Energy detection method

Energy detection (ED) method that is a basic sensing technique do not need any
prior knowledge about the PU signal. Therefore, this detection technique pro-
vides several advantages in terms of application and computation complexities.
The received energy is a measure of a particular part of the spectrum. The detec-
tor compares the measured energy with a threshold value to decide whether the
channel is available. This method needs longer sensing time in order to enhance
signal to noise ratio (SNR), which leads to high power consumption, and