A Survey on the Energy Detection of OFDM Signals with Dynamic Threshold Adaptation: Open Issues and Future Challenges  
[PERSON]  
1 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, 21000 Split, Croatia; [EMAIL_ADDRESS]  
2 Elektroprenoes-Elektroprienos BiH a.d. Banja Luka, 88000 Mostar, Bosnia and Herzegovina; [EMAIL_ADDRESS]  
[PERSON]  
2 Elektroprenoes-Elektroprienos BiH a.d. Banja Luka, 88000 Mostar, Bosnia and Herzegovina; [EMAIL_ADDRESS]  
[PERSON]  
1 Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture (FESB), University of Split, 21000 Split, Croatia; [EMAIL_ADDRESS]  
Footnote 1: email: {Ivana.Ramljak, 88000,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,,  
RF spectrum vary in both time and space domains [1; 2; 3]. Cognitive radio (CR) as a concept based on the ability to detect and share the unutilised spectrum has been envisioned as a promising candidate for improving policy related to the inefficient assignment of frequency spectrum [4]. In CR, spectrum sensing (SS) is seen as the most demanding process. The goal of SS is to detect the periods of inactivity of the licensed user, known as the primary user (PU), in a specific frequency band and, if this band is available, to enable transmission for an unlicensed user, known as a secondary user (SU), such that it does not interfere with the PU. Thus, the utilisation of an unutilised band by the SU in the moments when the PU is not active can significantly reduce the spectrum scarcity problem [5; 6]. Different approaches have been proposed in the literature for SS. Energy detection (ED) as one of the non-cooperative methods of SS is broadly considered due to its low computational complexity and simple implementation. The main advantage of the ED method is the fact that it does not include complex signal processing and does not require prior information about the PU signal. However, ED has some limitations, such as the need for a priori knowledge on the noise energy level or its reliable estimate, a susceptibility to the noise power uncertainty (also known as noise uncertainty (NU)), a poor performance below a certain value of Signal-to-Noise Ratio (SNR) level (known as noise floor level) and the lack of ability to distinguish between PU signals, SU signals and interference [3; 7]. In essence, the ED technique includes an estimation of the received signal energy at the receiver side and a comparison of the estimated energy, with a set threshold to confirm the presence or absence of the PU signal. The SS performance of the ED method depends greatly on the setting of the detection threshold [8]. Setting an appropriate threshold is a challenging task since it must differentiate among the PU signal and noise. Dynamic threshold (DT) adaptation and the fixed threshold approach are two main approaches to set the detection threshold of the PU signal in the ED process. A conventional energy detector uses a fixed threshold value to judge the occupation of the spectrum. In this case, regardless of the SNR fluctuations, the fixed threshold value does not change over time. The disadvantage of this approach is that the system requires prior knowledge of the noise level. The threshold is determined as the most appropriate and it is set manually as a static level above a noise floor. If the static threshold is set too high above the noise floor, the percentage of PUs that will remain undetected can increase, which may cause harmful interference from the SU to the PU. Hence, due to the fluctuating nature of the noise signals that exist in practice, this approach is susceptible to erroneous decision-making. Some fixed threshold techniques that have been proposed in the literature are histogram analysis, the empirical analysis of spectrum measurements, the receiver noise characteristics threshold and the P-tile-based threshold technique [9; 10; 11].