Analysis of the Impact of Detection Threshold Adjustments and Noise Uncertainty on Energy Detection Performance in MIMO-OFDM Cognitive Radio Systems

Abstract

Due to the capability of the effective usage of the radio frequency spectrum, a concept known as cognitive radio has undergone a broad exploitation in real implementations. Spectrum sensing as a core function of the cognitive radio enables secondary users to monitor the frequency band of primary users and its exploitation in periods of availability. In this work, the efficiency of spectrum sensing performed with the energy detection method realized through the square-law combining of the received signals at secondary users has been analyzed. Performance evaluation of the energy detection method was done for the wireless system in which signal transmission is based on Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing. Although such transmission brings different advantages to wireless communication systems, the impact of noise variations known as noise uncertainty and the inability of selecting an optimal signal level threshold for deciding upon the presence of the primary user signal can compromise the sensing precision of the energy detection method. Since the energy detection may be enhanced by dynamic detection threshold adjustments, this manuscript analyses the influence of detection threshold adjustments and noise uncertainty on the performance of the energy detection spectrum sensing method in single-cell cognitive radio systems. For the evaluation of an energy detection method based on the square-law combining technique, the mathematical expressions of the main performance parameters used for the assessment of spectrum sensing efficiency have been derived. The developed expressions were further assessed by executing the algorithm that enabled the simulation of the energy detection method based on the square-law combining technique in Multiple-Input Multiple-Output—Orthogonal Frequency Division Multiplexing cognitive radio systems. The obtained simulation results provide insights into how different levels of detection threshold adjustments and noise uncertainty affect the probability of detection of primary user signals. It is shown that higher signal-to-noise-ratios, the transmitting powers of primary user, the number of primary user transmitting and the secondary user receiving antennas, the number of sampling points and the false alarm probabilities improve detection probability. The presented analyses establish the basis for understanding the energy detection operation through the possibility of exploiting the different combinations of operating parameters which can contribute to the improvement of spectrum sensing efficiency of the energy detection method.

The novel approach to the closed-form average bit error rate calculation for the Nakagami-m fading channel

“…It can be pointed out that the solutions to a large number of modern wireless communications problems depend heavily on the normality assumption of some stochastic physical effects (e.g., reflection, multiple diffractions, fading); thus, the expressions with Gauss Q-function and its squared version naturally arise. An important example is the problem of signal detection with the help of the energy-based spectrum sensing procedure for ad hoc systems and networks, including polar-coding transmission for 5G [41], MIMO-OFDM Cognitive Radio Systems [42], listenbefore-talk procedure in 5G networks [43], etc.…”

Comparative analysis of blind detectors in a cluster-based cooperative Spectrum Hole detection

“…However, spectrum usage is a function of time and most of the assigned spectrum is not utilized over a considerable period resulting in under exploitation of the assigned spectrum. Therefore, fixed spectrum access policy is no longer a viable approach to meet up with the rapid growing demand of frequency spectrum to support emerging wireless applications (Jayanta et al, 2014;Saeid et al, 2013;Ojo et al, 2021;Samrat and Ajitsinh, 2016;Josip et al, 2022). Spectrum Sharing (SSH) technique known as Cognitive Radio (CR) has emerged as a promising technique to tackle the underutilization of the assigned spectrum through a Dynamic Spectrum Access (DSA).…”

“…AU owns the privileges to the assigned spectrum, while, CU is Unauthorized User (UAU) that makes use of the spectrum when it is idle. The SSH improves spectrum utilization by enabling CU to access the assigned spectrum without interfering with the AU [Ojo et al, 2020;Runze et al, 2019;Ojo and Fagbola, 2015;Jingwen et al, 2018;Hayking, 2005].…”