Robust Statistics Evidence Based Secure Cooperative Spectrum Sensing for Cognitive Radio Networks

Simpson, Oluyomi; Sun, Yichuang

doi:10.1109/iwcmc48107.2020.9148381

Cited by 7 publications

(4 citation statements)

References 13 publications

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“…It is well known that the ED method has a low linear computational complexity, which is usually considered as O(N). Comparing equation (17) with equation ( 5), it is clear that this proposed method has MN − 1 more addition operations, one more division operation, one more subtraction operation, and N more squaring operations than ED which only needs MN − 1 addition and MN squaring operations.…”

Section: Energy Detection-based Spectrum-sensing Methods With Multipl...mentioning

confidence: 99%

“…In the CSD method, compressive sensing can be used to determine the symmetrical cycle frequency [14], while Fourier transform can be used to obtain the characteristic function of the cycle frequency [15]. In addition, the cooperative spectrum sensing [16,17] can further improve the overall performance of spectrum sensing in CR networks, and some artificial intelligence methods have been also applied in spectrumsensing or spectrum signal classification [18][19][20].…”

Section: Introductionmentioning

confidence: 99%

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An Energy Detection-Based Spectrum-Sensing Method for Cognitive Radio

Luo

Zhang

Yan

2022

Wireless Communications and Mobile Computing

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Energy detection (ED) method is one of the most commonly used signal-sensing methods in spectrum sensing due to its low implementation complexity. ED can achieve good detection performance when the noise variance is known. However, in most cases, the noise variance is estimated, which may result in the uncertainty in noise variance. In the presence of noise variance uncertainty, the detection performance of the ED method may degrade significantly. To reduce the impact of uncertainty in noise variance, an ED-based sensing method is proposed in this paper. This method combines these signal samples sampled by multiple antennas to obtain the decision statistic as ED does. A novel technique is proposed to construct the decision threshold so that it is independent of the noise variance. As a consequence, the proposed method is free of the effect of noise variance uncertainty, and the noise variance estimation is not need. The simulation results show that the detection probability of this method can approach to 1 even when the SNR is −15 dB while the detection probability of ED is below 0.8, which means the detection performance of the proposed method can outperform the ED method without the noise variance estimation when the number of antennas is greater than two.

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Section: Energy Detection-based Spectrum-sensing Methods With Multipl...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An Energy Detection-Based Spectrum-Sensing Method for Cognitive Radio

Luo

Zhang

Yan

2022

Wireless Communications and Mobile Computing

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“…The fading is assumed to vary identically during the transmission of at least two consecutive information blocks. Here, it is assumed that the cooperating nodes [34][35][36] and the destination are unable to acquire CSI. Thus, they recover the transmitted bits from consecutively received signals.…”

Section: Performance Evaluationmentioning

confidence: 99%

Co-Efficient Vector Based Differential Distributed Quasi-Orthogonal Space Time Frequency Coding

Nwanekezie,

Simpson,

Owojaiye

et al. 2023

Sensors

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Distributed space time frequency coding (DSTFC) schemes address problems of performance degradation encountered by cooperative broadband networks operating in highly mobile environments. Channel state information (CSI) acquisition is, however, impractical in such highly mobile environments. Therefore, to address this problem, designers focus on incorporating differential designs with DSTFC for signal recovery in environments where neither the relay nodes nor destination have CSI. Traditionally, unitary matrix-based differential designs have been used to generate the differentially encoded symbols and codeword matrices. Unitary based designs are suitable for cooperative networks that utilize the amplify-and-forward protocol where the relay nodes are typically required to forego differential decoding. In considering other scenarios where relay nodes are compelled to differentially decode and re-transmit information signals, we propose a novel co-efficient vector differential distributed quasi-orthogonal space time frequency coding (DQSTFC) scheme for decode-and-forward cooperative networks. Our proposed space time frequency coding scheme relaxes the need for constant channel gain in the temporal and frequency dimensions over long symbol periods; thus, performance degradation is reduced in frequency-selective and time-selective fading environments. Simulation results illustrate the performance of our proposed co-efficient vector differential DQSTFC scheme under different channel conditions. Through pair-wise error probability analysis, we derive the full diversity design criteria for our code.

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“…Pooja et al explained about the detection of Byzantine attack by using density‐based method in Reference 28. In Reference 29, Simpson and Sun proposed a CSS scheme in which the presence and absence hypotheses distribution of PU signal is estimated based on past sensing received energy data incorporating robust statistics, and the data fusion is performed according to an evidence‐based approach 30,31 . proposed a faithworthy CSS scheme based on the D‐S theory of evidence and holistic to effectively defend against Byzantine attack.…”

Section: Introductionmentioning

confidence: 99%

Robust and efficient cooperative spectrum sensing against probabilistic hard Byzantine attack

Chen

Gan

et al. 2021

Trans Emerging Tel Tech

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Cognitive radio (CR) is regarded as a powerful technology to solve the problem of spectrum shortage and underutilization. As a key function of CR technology, cooperative spectrum sensing (CSS) allows secondary users (SUs) to detect the primary user (PU)'s signal so that they identify and opportunistically access the available spectrum. However, the openness of CSS paradigm makes cognitive radio networks (CRNs) suffer from Byzantine attack, thereby undermining the premise of CR framework. To this aim, we formulate a probabilistic hard Byzantine attack model, in which malicious users (MUs) can conduct various attack strategies, and make an in‐depth investigation on the blind scenario. On the one hand, in order to ensure the robustness of CSS, a method to evaluate the reliability of the secondary user (SU)'s sensing result based on the channel status detection is proposed and an innovative weight coefficient is considered to selectively utilize the sensing information from MUs. On the other hand, we design a sequential fusion method based on reputation value (RV) and differential mechanism, with the aim of improving the efficiency of CSS. According to above methods and mechanism, the weighted differential sequential symbol (WDS2) algorithm is designed, which integrates the weight evaluation into sequential method to make the global decision for CSS. Finally, compared to the existing various data fusion algorithms, simulation results show that the proposed WDS2 not only defends against various Byzantine attacks to secure the robustness of CSS, but also requires less samples in support of an accurate global decision to improve the efficiency of CSS.

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Robust Statistics Evidence Based Secure Cooperative Spectrum Sensing for Cognitive Radio Networks

Cited by 7 publications

References 13 publications

An Energy Detection-Based Spectrum-Sensing Method for Cognitive Radio

An Energy Detection-Based Spectrum-Sensing Method for Cognitive Radio

Co-Efficient Vector Based Differential Distributed Quasi-Orthogonal Space Time Frequency Coding

Robust and efficient cooperative spectrum sensing against probabilistic hard Byzantine attack

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