Abstract
When a primary user uses frequency hopping communication, cognitive radio users using typically spectrum detection method is the time-domain autocorrelation. But the primary users signal is interfered by a fixed-frequency interference (FFI), the method is invalid. For the problem, this paper improves the traditional time-domain autocorrelation method by using the power spectrum cancellation, and the improved method can effectively avoid the fixed-frequency spectrum interference to increase the spectrum detection performance. Simulation results show that signal-to-noise ratio (SNR) is below −10 dB, and the false alarm probability is 0.05, the detection probability of improved method is greater than that of the traditional time-domain autocorrelation method. In low SNR, the improved method has a good detection performance, and also can prevent the collision between frequency of FFI and frequency of the primary user as well.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Wang SB, Zhou Z, Kwak KY (2012) Two pulse designs for ultra wideband-cognitive radio by using multiple modified transform domain communication system. Appl Math Inform Sci 6:619–628
Haykin S (2005) Cognitive radio: brain-empowered wireless communications. IEEE J Select Areas Commun 23:201–220
Gao XJ, Li DX et al (2008) Algorithm for frequency-hopping signal detection based on suppressing power spectrum. J Jilin University 26:239–243
Chung CD (1994) Generalised likelihood-ratio detection of multiple-hop frequency-hopping signals. IEE Proc Commun 141:70–78
Chung CD, Polydors A (1995) Parameter estimation of random FH signals using autocorrelation techniques. IEEE Trans Commun 43:1097–1106
Barbarossa S, Scaglione A (1997) Parameter estimation of spread spectrum frequency hopping signals time–frequency distribution. In: Proc of first IEEE signal processing workshop on signal processing advance in wireless communications, pp 213–216
Lavielle M (1998) Optimal segmentation of random processes. IEEE Sign Proc 46:1365–1373
Norbert W (1930) Generalized harmonic analysis. Acta Math 55:117–258
Acknowledgments
Shubin Wang (wangsb09@gmail.com) is the correspondent author and this work was supported by the National Natural Science Foundation of China (61261020), and the Natural Science Foundation of Inner Mongolia, China (2012MS0903), and the Scientific Research Initial Fund for Higher Talents Program of Inner Mongolia University, China.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2015 Springer International Publishing Switzerland
About this paper
Cite this paper
Liu, S., Wang, S., Wang, H., Liu, H. (2015). An Improved Time-Domain Autocorrelation Spectrum Detection Algorithm. In: Mu, J., Liang, Q., Wang, W., Zhang, B., Pi, Y. (eds) The Proceedings of the Third International Conference on Communications, Signal Processing, and Systems. Lecture Notes in Electrical Engineering, vol 322. Springer, Cham. https://doi.org/10.1007/978-3-319-08991-1_36
Download citation
DOI: https://doi.org/10.1007/978-3-319-08991-1_36
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-08990-4
Online ISBN: 978-3-319-08991-1
eBook Packages: EngineeringEngineering (R0)