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.

Signal detection with spectrum windows

“…Indeed, with window shapes and , the correlation at the adjacent bin is (about) 1/9 and 1/16, respectively, and zero in other bins [19] . Correlation within sliding window energy detection has been considered in [20] but that method is not directly applicable herein. Moreover, the leakage level is rather low, below -15 dB, if a reasonable fast Fourier transform (FFT) size is used [18] .…”

Game theoretic power allocation and waveform selection for satellite communications

“…Moreover, QoS methods [16,17] for efficient routing of data were discussed. There are several communication methods including tracking [18], energy detection [19], cloud computing [20], and frequency hopping [21]. Target tracking [22], network survivability [23], and resource management [24] can be supported by the communication methods mentioned above.…”

Mitigation of weather on channel propagation for satellite communications

“…Moreover, QoS methods [19,20] for efficient routing of data were discussed. There are several communication methods including energy detection [21], cloud computing [22], and frequency hopping [23]. Target tracking [24], network survivability [25], and resource management [26] can also be supported by the communication methods mentioned above.…”