Eigenvalue-based Detection Techniques Using Finite Dimensional Complex Random Matrix Theory: A Review


Detection of primary users without requiring information of signal is of great importance in spectrum sensing (SS) in Cognitive Radio. Therefore, in recent years, eigenvalue based spectrum sensing algorithms are under the spotlight. Many primary user detection techniques have been proposed for use in Cognitive Radio (CR) and their drawbacks and benefits have been examined. However, among the various methods proposed, only some of them can survive in an antagonistic environment. Therefore, another appealing side of eigenvalue based primary user detection algorithms is the fact that they are totally immune to uncertain noise levels so they are called robust detectors. Random matrix theory (RMT) is a useful tool which is applicable across a large number of fields and in the last decade, a considerable applications in signal detection has emerged. In this paper, the detection performances of the eigenvalue based techniques are analyzed based on the exact threshold formulations using RMT. As opposed to the threshold estimations with large number of samples and antennas presented in the literature, the exact thresholds are used for finite number of samples and antennas. The importance of accurate decision threshold selection in spectrum sensing is emphasized. It is shown that the accurate threshold computations enable the achievement of higher detection performances than asymptotic analyses reported in the literature.

Authors and Affiliations

Ayse Kortun


Related Articles

Multi-Radio 5G Architecture for Connected and Autonomous Vehicles: Application and Design Insights

Connected and Autonomous Vehicles (CAVs) will play a crucial role in next-generation Cooperative Intelligent Transportation Systems (C-ITSs). Not only is the information exchange fundamental to improve road safety and ef...

Tele-Monitoring the Battery of an Electric Vehicle

Nowadays, transportation is one of the main air pollution sources and has a significant impact on human health and environmental quality. The electric vehicle is a zero emission vehicle powered by an electric motor with...

An Analysis of Increased Vertical Scaling in Three-Dimensional Virtual World Simulation

In this paper, we describe the analysis of the effect of vertical computational scaling on the performance of a simulation based training prototype currently under development by the U.S. Army Research Laboratory. The Un...

Split and Merge Strategies for Solving Uncertain Equations Using Affine Arithmetic

The behaviour of systems is determined by various parameters. Due to several reasons like e. g. manufacturing tolerances these parameters can have some uncertainties. Corner Case and Monte Carlo simulations are well know...

Merging OMG Standards in a General Modeling, Transformation, and Simulation Framework

Test-driven Agile Simulation (TAS) is a general-purpose approach that combines model-driven engineering, simulation, and testing techniques to improve overall quality for the development process. TAS focuses on the const...

Download PDF file
  • EP ID EP46079
  • DOI http://dx.doi.org/10.4108/eai.27-6-2018.154834
  • Views 202
  • Downloads 0

How To Cite

Ayse Kortun (2018). Eigenvalue-based Detection Techniques Using Finite Dimensional Complex Random Matrix Theory: A Review. EAI Endorsed Transactions on Industrial Networks and Intelligent Systems, 5(14), -. https://europub.co.uk/articles/-A-46079