Proceedings ArticleDOI
Robust Distributed Spectrum Sensing in Cognitive Radio Networks
Ruiliang Chen,Jung-Min Park,Kaigui Bian +2 more
- pp 1876-1884
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TLDR
This work proposes a new data fusion technique that uses a variable number of samples, and introduces a reputation-based mechanism to the Sequential Probability Ratio Test (SPRT), which is evaluated by comparing it with a variety of data fusion techniques under various network operating conditions.Abstract:
Distributed spectrum sensing (DSS) enables a Cognitive Radio (CR) network to reliably detect licensed users and avoid causing interference to licensed communications. The data fusion technique is a key component of DSS. We discuss the Byzantine failure problem in the context of data fusion, which may be caused by either malfunctioning sensing terminals or Spectrum Sensing Data Falsification (SSDF) attacks. In either case, incorrect spectrum sensing data will be reported to a data collector which can lead to the distortion of data fusion outputs. We investigate various data fusion techniques, focusing on their robustness against Byzantine failures. In contrast to existing data fusion techniques that use a fixed number of samples, we propose a new technique that uses a variable number of samples. The proposed technique, which we call Weighted Sequential Probability Ratio Test (WSPRT), introduces a reputation-based mechanism to the Sequential Probability Ratio Test (SPRT). We evaluate WSPRT by comparing it with a variety of data fusion techniques under various network operating conditions. Our simulation results indicate that WSPRT is the most robust against the Byzantine failure problem among the data fusion techniques that were considered.read more
Citations
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Journal ArticleDOI
Cooperative spectrum sensing in cognitive radio networks: A survey
TL;DR: The state-of-the-art survey of cooperative sensing is provided to address the issues of cooperation method, cooperative gain, and cooperation overhead.
Journal ArticleDOI
Advances in cognitive radio networks: A survey
Beibei Wang,K.J.R. Liu +1 more
TL;DR: Recent advances in research related to cognitive radios are surveyed, including the fundamentals of cognitive radio technology, architecture of a cognitive radio network and its applications, and important issues in dynamic spectrum allocation and sharing are investigated in detail.
Journal ArticleDOI
Distributed Spectrum Sensing for Cognitive Radio Networks by Exploiting Sparsity
TL;DR: A cooperative approach to the sensing task of wireless cognitive radio (CR) networks is introduced based on a basis expansion model of the power spectral density map in space and frequency that reduces spatial and frequency spectrum leakage by 15 dB relative to least-squares alternatives.
Journal ArticleDOI
What is a Spectrum Hole and What Does it Take to Recognize One
TL;DR: These new metrics are used to show that fading uncertainty forces the WPAR performance of single-radio sensing algorithms to be very low for small values of F HI, even for ideal detectors.
Journal ArticleDOI
A Survey on Security Threats and Detection Techniques in Cognitive Radio Networks
TL;DR: The scope of this work is to give an overview of the security threats and challenges that cognitive radios and cognitive radio networks face, along with the current state-of-the-art to detect the corresponding attacks.
References
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Proceedings ArticleDOI
A scalable dynamic spectrum allocation system with interference mitigation for teams of spectrally agile software defined radios
TL;DR: A robust method for estimating locally the unused or underutilized regions of RF spectrum to optimize dynamic spectrum usage and the effect on reducing the risk of interference by collaborating across multiple nodes that provides increased robustness of sensing of open spectrum through spatial diversity is presented.
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TL;DR: A key component of such Spectrum Agile Radio (SARA) systems, namely, the detection of spectrum opportunities is focused on, and results of simulation studies of the use of Hough Transform and autocorrelation function are presented.