Sliding window energy detection for spectrum sensing under low SNR conditions
Abstract
For spectrum sensing, energy detection has the advantages of low complexity, rapid analysis, and requires no knowledge of the transmission signal, which makes it suitable for a wide range of applications. However, under low signal‐to‐noise ratio conditions, the required window length (or the time‐bandwidth product) for energy detection to achieve a desired detection performance is large. In addition, conventional energy detection assumes that the detection tests are independent, that is, there is no overlap between individual detection tests. These properties significantly reduce the detection speed when energy detection is used for the continuous monitoring over a communication channel for the detection of signal transmission activities. In this paper, we propose a sliding window detection analysis with overlap among multiple tests. Algorithms for effective performance analysis of the proposed sliding window energy detection are proposed. The impact of window length on distribution of detection time is investigated. Simulation results on the proposed sliding window energy detection are also compared with the theoretically predicted and conventional energy detection performance estimates. Copyright © 2015 John Wiley & Sons, Ltd.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Oct 29, 2015
- Source ID
- 10.1002/wcm.2639
Entities
People
- Dan Shen
- Erik Blasch
- Genshe Chen
- Khanh Pham
- Xin Tian
- Zhi Tian
Organizations
- Air Force Research Laboratory
- George Mason University
- United States Air Force