Spectrum sensing using multiple large eigenvalues and its performance analysis

Ming Jin, Qinghua Guo, Youming Li, Jiangtao Xi, Defeng Huang

Research output: Contribution to journalArticle

4 Citations (Scopus)

Abstract

Cognitive radio (CR) is a promising technology to address the challenge of spectrum scarcity due to the massive number of objects in the Internet of Things (IoT). Equipping IoT objects with CR capability can also alleviate interference situations and achieve seamless connectivity in IoT. This work deals with CR spectrum sensing and proposes a new eigenvalue-based detector by exploiting the summation of multiple large eigenvalues of the covariance matrix of received signals. By analyzing the distribution of the sum of the dependent large eigenvalues, we derive an approximate but explicit expression for the theoretical performance of the proposed detector. The theoretical analysis of the proposed detector is validated and its superior performance is demonstrated with real world signals. It is shown that the proposed detector outperforms the existing eigenvalue-based detectors and is more robust against noise uncertainty.

Original languageEnglish
Article number8412084
Pages (from-to)776-789
JournalIEEE Internet of Things Journal
Volume6
Issue number1
Early online date17 Jul 2018
DOIs
Publication statusPublished - Feb 2019

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