Spectrum Sensing Detection for Non-Stationary Primary User Signals Over Dynamic Threshold Energy Detection in Cognitive Radio System

  • Akil Al-Wotaifi Ministry of Telecommunications, Republic of Iraq
  • Bashar J. Hamza Communications Tech. Eng. Dept., Al-Najaf Technical Engineering College, Al-Furat Al-Al-Awsat Technical University ATU, Al-Najaf, Republic of Iraq
  • Wasan Kadhim Saad Communications Tech. Eng. Dept., Al-Najaf Technical Engineering College, Al-Furat Al-Al-Awsat Technical University ATU, Al-Najaf, Republic of Iraq
Keywords: Active period, Dynamic Energy Detection-Dynamic threshold, Low SNR, Non-stationary user

Abstract

The modern-day global evolution and technological revolution of wireless communication development, without observing the current radio spectrum assignment policy, cause the spectrum to be more depleted. Cognitive radio is the most effective technique for solving the problem of spectrum scarcity, particularly in light of the desire to transmit data very quickly, as unauthorized users are able to use a spectral bandwidth. Whenever the owner of the license begins to use the domain, the connection of the unauthorized user will be cut until the authorized user ends his connection. Conventional methods have proven to be ineffective in detecting the frequency spectrum in comparison to dynamic primary user methods, where the primary user is either completely present or completely absent. In this paper, an algorithm is suggested which aims to improve energy sensing and increases the efficiency of detection through sensing and noticing the random dynamic move of the primary user. This algorithm has been designed based on these rapid changes of the primary user, and is called the Activity period (A). In addition to activities of the primary user during the sensing period, it also focuses on the dynamic threshold factor through which the detector is enhanced. The new formula is applied through the Dynamic Energy Detection-Dynamic Threshold (DED-DT) method with a constant false alarm rate analyzed mathematically, realizing a reliable performance with a low signal-to-noise ratio (-12 dB) achieved through simulation. Therefore, the proposed algorithm showed relatively improved results when compared to those of traditional detection methods.

Published
2020-04-11