College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China.
Sensors (Basel). 2018 Dec 11;18(12):4377. doi: 10.3390/s18124377.
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.
频谱感知在认知无线电网络中的未用频谱检测中起着至关重要的作用，包括协作频谱感知（CSS）和独立频谱感知。在认知无线电 ad hoc 网络（CRAHNs）中，CSS 通过探索频谱局部同质性并充分利用相邻节点的知识（例如，感知结果和拓扑信息）来增强认知节点的感知性能。然而，CSS 也可能为恶意节点（即频谱感知数据伪造（SSDF）攻击者）打开大门，这些攻击者会报告虚假的感知结果，从而降低 CSS 的性能。通常，CSS 的性能与 SSDF 攻击者的分数呈反比。相反，独立频谱感知对 SSDF 攻击具有鲁棒性。因此，对于与各种 SSDF 攻击者分数共存的 CRAHNs，选择独立感知和协作感知之间的适当感知策略是可取的。在本文中，提出了一种称为频谱感知策略选择（4S）的新算法，以协作或独立方式选择更好的感知策略。为了得出节点频谱状态的最大后验估计，我们研究了基于图割的 CSS 方法，通过该方法构建了拓扑信息代价函数和感知结果代价函数。此外，还应用了声誉值来评估 CSS 和独立感知的性能。从理论上分析了声誉阈值，以最小化选择性能较差的感知方式的概率。进行了仿真以验证所提出算法的可行性和效率。
