Abstract
Spectrum sensing plays an essential role in the detection of unused spectrum whole in cognitive radio networks, including cooperative spectrum sensing (CSS) and independent spectrum sensing. In cognitive radio ad hoc networks (CRAHNs), CSS enhances the sensing performance of cognitive nodes by exploring the spectrum partial homogeneity and fully utilizing the knowledge of neighboring nodes, e.g., sensing results and topological information. However, CSS may also open a door for malicious nodes, i.e., spectrum sensing data falsification (SSDF) attackers, which report fake sensing results to deteriorate the performance of CSS. Generally, the performance of CSS has an inverse relationship with the fraction of SSDF attackers. On the contrary, independent spectrum sensing is robust to SSDF attacks. Therefore, it is desirable to choose a proper sensing strategy between independent sensing and collaborative sensing for CRAHNs coexisting with various fractions of SSDF attackers. In this paper, a novel algorithm called Spectrum Sensing Strategy Selection (4S) is proposed to select better sensing strategies either in a collaborative or in an independent manner. To derive the maximum a posteriori estimation of nodes’ spectrum status, we investigated the graph cut-based CSS method, through which the topological information cost function and the sensing results cost function were constructed. Moreover, the reputation value was applied to evaluate the performance of CSS and independent sensing. The reputation threshold was theoretically analyzed to minimize the probability of choosing the sensing manner with worse performance. Simulations were carried out to verify the viability and the efficiency of the proposed algorithm.
Highlights
With the rapid development of radio communication, radio systems tend to provide higher speed, have denser deployment, and occupy wider bandwidth, which can cause the radio spectrum to become overcrowded, i.e., spectrum scarcity
This paper proposes a spectrum sensing strategy selection algorithm based on the reputation value theory
Where PbCi and PbiI denote the sensing error of cooperative spectrum sensing (CSS) and the sensing error of independent sensing, respectively; κ i = 0 and κ i = 1 indicate that the CSS results are selected and that the independent sensing results are selected for i-th secondary users (SUs), respectively
Summary
With the rapid development of radio communication, radio systems tend to provide higher speed, have denser deployment, and occupy wider bandwidth, which can cause the radio spectrum to become overcrowded, i.e., spectrum scarcity. Reputation value theory (RVT)-based algorithms against SSDF attacks are commonly applied in cognitive radio networks to detect and remove malicious nodes [11,12]. The independent sensing results, which perform better when the fraction of SSDF attackers is high, are not used in the proposed algorithm [14]. Different from previous researches, this paper mainly concentrates on the problem of choosing the sensing strategy between either independent spectrum sensing or CSS from the view of honest Sus, rather than how to reject malicious nodes from the view of the data fusion center. This paper proposes a spectrum sensing strategy selection algorithm based on the reputation value theory.
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