Software-defined routing protocol for mobile cognitive radio networks : a cross-layer perspective

The growing demand for wireless applications, combined with inefficient spectrum use, necessitates developing a new wireless communication paradigm that focuses on dynamic spectrum access rather than the fixed spectrum using cognitive radio technology. The unlicensed user, known as secondary user or cognitive user, uses cognitive radio technology to grow opportunistic communication over licensed spectrum bands and improve spectrum management performance. The routing protocol in Cognitive Radio Networks (CRNs) serves as a communication backbone, allowing data packets to transfer between cognitive user nodes through multiple paths and channels. However, the problem of routing in CRNs is to create a robust-stable route over higher channel availability. The previously developed protocols missed opportunities to exploit the time-variant channel estimation technique, which selects the best route using the cross-layer routing decision engine to track the adverse impact of cognitive user mobility and primary user activity. This study aims to construct a robust routing path while limiting interference with primary user activity, delaying routing, and maximizing routing throughput. Here, a new routing framework is created in this study to explore new extended routing functions and features from the lower layers (Physical layer and Data Link layer) feedback to improve routing performance. Then, the link-oriented channel availability and channel quality have been developed based on two reliable metrics, which are channel availability probability and channel quality, to estimate and select a channel that maximizes link-throughput. Furthermore, this study proposes a novel cross layer routing protocol, namely, the Software-Defined Routing Protocol. It is a cross-layer method to combine the lower layer (Physical layer and Data Link layer) sensing derived from the channel estimation model. It periodically updates the routing table for optimal route decision making. The output simulation of the channel estimation method has shown that it has produced a powerful channel selection strategy to maximize the average rate of link throughput and achieved a channel estimate under the time-variant effect. Extensive simulation experiments have been performed to evaluate the proposed protocol in compression with the existing benchmark protocols, namely, dual diversity cognitive Ad-hoc routing protocol and cognitive Ad-hoc on-demand distance vector. The proposed protocol outperforms the benchmarks, resulting in increasing the packet delivery ratio by around (11.89%-12.80%), reducing delay by around (2.74%-4.05%), reducing overhead by around (14.31%-18.36%), and increasing throughput by around (23.94%-28.35%). The software-defined routing protocol, however, lacks the ability to determine the better idle channel at high-speed node mobility. In conclusion, the cross-layer routing protocol successfully achieves high routing performance in finding a robust route, selecting high channel stability, and reducing the probability of interference with primary users for continued communication

Cognitive Radio for Emergency Networks

In the scope of the Adaptive Ad-hoc Freeband (AAF) project, an emergency network built on top of Cognitive Radio is proposed to alleviate the spectrum shortage problem which is the major limitation for emergency networks. Cognitive Radio has been proposed as a promising technology to solve todayâ?~B??~D?s spectrum scarcity problem by allowing a secondary user in the non-used parts of the spectrum that aactully are assigned to primary services. Cognitive Radio has to work in different frequency bands and various wireless channels and supports multimedia services. A heterogenous reconfigurable System-on-Chip (SoC) architecture is proposed to enable the evolution from the traditional software defined radio to Cognitive Radio

Byzantine Attack and Defense in Cognitive Radio Networks: A Survey

The Byzantine attack in cooperative spectrum sensing (CSS), also known as the spectrum sensing data falsification (SSDF) attack in the literature, is one of the key adversaries to the success of cognitive radio networks (CRNs). In the past couple of years, the research on the Byzantine attack and defense strategies has gained worldwide increasing attention. In this paper, we provide a comprehensive survey and tutorial on the recent advances in the Byzantine attack and defense for CSS in CRNs. Specifically, we first briefly present the preliminaries of CSS for general readers, including signal detection techniques, hypothesis testing, and data fusion. Second, we analyze the spear and shield relation between Byzantine attack and defense from three aspects: the vulnerability of CSS to attack, the obstacles in CSS to defense, and the games between attack and defense. Then, we propose a taxonomy of the existing Byzantine attack behaviors and elaborate on the corresponding attack parameters, which determine where, who, how, and when to launch attacks. Next, from the perspectives of homogeneous or heterogeneous scenarios, we classify the existing defense algorithms, and provide an in-depth tutorial on the state-of-the-art Byzantine defense schemes, commonly known as robust or secure CSS in the literature. Furthermore, we highlight the unsolved research challenges and depict the future research directions.Comment: Accepted by IEEE Communications Surveys and Tutoiral