Sequential Cooperative Spectrum Sensing Research Articles

Sequential cooperative spectrum sensing in the presence of dynamic Byzantine attack for mobile networks.

Cooperative spectrum sensing (CSS) is envisaged as a powerful approach to improve the utilization of scarce radio spectrum resources, but it is threatened by Byzantine attack. Byzantine attack has been becoming a popular research topic in both academia and industry due to the demanding requirements of security. Extensive research mainly aims at mitigating the negative effect of Byzantine attack on CSS, but with some strong assumptions, such as attackers are in minority or trusted node(s) exist for data fusion, while paying little attention to a mobile scenario. This paper focuses on the issue of designing a general and reliable reference for CSS in a mobile network. Instead of the previously simplified attack, we develop a generic Byzantine attack model from sophisticated behaviors to conduct various attack strategies and derive the condition of which Byzantine attack makes the fusion center (FC) blind. Specifically, we propose a robust sequential CSS (SCSS) against dynamic Byzantine attack. Our proposed method solves the unreliability of the FC by means of delivery-based assessment to check consistency of individual sensing report, and innovatively reuses the sensing information from Byzantines via a novel weight allocation mechanism. Furthermore, trust value (TrV) ranking is exploited to proceed with a sequential test which generates a more accurate decision about the presence of phenomenon with fewer samples. Lastly, we carry out simulations on comparison of existing data fusion technologies and SCSS under dynamic Byzantine attack, and results verify the theoretical analysis and effectiveness of our proposed approach. We also conduct numerical analyses to demonstrate explicit impacts of secondary user (SU) density and mobility on the performance of SCSS.

Sequential Cooperative Spectrum Sensing Technique in Time Varying Channel

Cognitive radio opportunistically accesses the spectrum while the licensed user is idle. A spectrum sensing procedure to monitor primary users' existence is therefore vital to cognitive radios. In this paper, we investigate the energy detection based sequential cooperative spectrum sensing technique in time varying channels. By utilizing past local observations from previous sensing slots, cognitive radio nodes can aggregate the current and previously received energy values to improve the detection performance. We propose the weighted sequential energy detector (SED) in which a fixed number of past observations are taken for decision making. In addition, we propose two adaptive schemes, namely the Two-Stage SED and the Differential SED, where a cognitive radio user uses previously received energy values until it detects a change in primary user's activity. The probability of false alarm and detection for the Weighted SED and Two-Stage SED schemes are derived. The results show that the proposed schemes achieve better detection performance over the conventional cooperative energy detection technique. In particular, the Two-Stage SED and Differential SED schemes can satisfy the IEEE 802.22 standard's requirement of 10% false alarm and 90% detection in scenarios that conventional techniques cannot accommodate.

A cluster-based sequential cooperative spectrum sensing scheme utilizing reporting framework for cognitive radios

The cognitive radio (CR) technology is being considered as a novel approach for improving the spectrum utilization by detecting and using the vacant spectrum bands of licensed users. Cooperative spectrum sensing (CSS) is the most promising method for offering more reliable sensing performance compared to individual sensing. However, in a large CR network, CSS requires a huge number of sensing result transmissions from cognitive radio users (CUs) to the fusion center (FC), which can result in overhead traffic of the control channel and lack of power consumption of the CUs. In this paper, we propose a cluster-based sequential cooperative spectrum sensing (SCSS) scheme utilizing a reporting framework to reduce the number of direct reports from CUs to FC while keeping similar sensing performance as the conventional CSS. By using the proposed scheme, the power consumption in the sensing process and the overhead of the control channel can be significantly reduced. Simulation proves the efficiency of the proposed scheme. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Optimal Truncated Ordered Sequential Cooperative Spectrum Sensing in Cognitive Radio

The cost for increasing the accuracy of cooperative spectrum sensing in cognitive radio requires a long time for collecting sensing data. Sequential fusion, in which the sensing data reports are sequentially collected, combined, and tested with two thresholds for deciding to wait for the next data report or concluding the presence or absence of the primary signal, is considered to reduce the collecting time. A further reduction in the average sequential report number (ASN) can be achieved by arranging the reports in descending order of data quality where the better sensing data is reported earlier. In this paper, the ASN and the error probability of the ordered sequential fusion are analytically calculated based on the direct method. The results are then adopted to design an optimal method for obtaining the optimal sequential thresholds and truncated point. The optimal truncated point enables one to minimize the ASN by discarding the sensing data with low quality, while the optimal sequential thresholds ensure the maintaining of the sensing performance of sequential fusion be the same level to that of the conventional parallel fusion.

A sequential cooperative spectrum sensing scheme based on cognitive user reputation

The spectrum sensing plays an essential role in Cognitive Radio (CR), which enables opportunistic access to underutilized licensed spectrums. Cooperative spectrum sensing can help improve sensing performance. However, when the number of cognitive users is large, the latency and network traffic for reporting sensing results to the Fusion Center (FC) become extremely large, which may result in an extended sensing time and collision in the control channel between Cognitive Users (CUs) and the FC. In this paper, we propose an extended Sequential Cooperative Spectrum Sensing (SCSS) scheme in which the reputation of individual CU is used to ensure that the FC efficiently collects local sensing data from CUs. The proposed scheme reduces the number of sensing reports required while improving sensing performance in comparison with the conventional SCSS scheme even when few malicious users exist in the network.