Wideband signal detection for cognitive radio applications with limited resources

• Main Authors: Shaoyang Men, Pascal Chargé, Yide Wang, Jianzhong Li
• Format: Article
• Language: English
• Published: SpringerOpen 2019-01-01
• Series: EURASIP Journal on Advances in Signal Processing
• Subjects: Wideband signal detection; Cognitive radio; Small sample size; Dempster-Shafer theory of evidence
• Online Access: http://link.springer.com/article/10.1186/s13634-018-0600-6

Abstract Wideband signals are expected to be used to achieve the required quality of service (QoS) in the next generation of wireless communications, civil and military radar, and many wireless sensor network (WSN) scenarios. Wideband signal detection has been identified as one of the most challenging problems in the proliferation of the cognitive radio technology. Moreover in many applications, spectrum sensing in cognitive radio (CR) is expected to be performed with limited resources in terms of time, computation, and complexity. This paper is dedicated to the detection of a wideband signal with small sample size. Aiming at using small sample size, a statistical model of samples is given based on Student’s t distribution. However, the limited number of channel observations brings a reduction of confidence in the decision. A set of new basic probability assignments associated with the hypothesis of the occupied or vacant channel are then proposed to perform the Dempster-Shafer (D-S) decision process. Simulation results show that the proposed method has much higher sensitivity to sense an occupied channel than the traditional energy detection method (ED) and the decision fusion method when small sample size is used.