Achieving RF Jamming with DSA-Enabled Cognitive Radio Swarms: A Guide to Trends, Technologies, and Approaches in the Information Sciences

Achieving RF Jamming with DSA-Enabled Cognitive Radio Swarms: A Guide to Trends, Technologies, and Approaches in the Information Sciences

Robert L. Foster Jr. (Lakota Technical Solutions, Inc., USA)
DOI: 10.4018/978-1-4666-5063-3.ch005


Recent studies prove that the current method of statically allocating and assigning RF spectrum is restrictive and inefficient and identify Dynamic Spectrum Access (DSA) as a feasible alternative. The author defines a system design which implemenst a declarative policy language using Semantic Web technologies. Swarms of multi-band, reconfigurable Cognitive Radio (CR) technology with fast channel switching and real time spectrum sensing capabilities have been identified as candidates for Multi-Channel Jamming Electronic Attacks (EA). Past demonstrations have shown that a single CR can be deployed in an EA on 802.11 networks. To extend the behavior of CRs beyond single multi-channel jamming, this chapter introduces a system architecture design that relies on a minimal set of CR capabilities to reduce the cost of designing the system.
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2. Background

The evolution of software defined radio (SDR) has led to significant advances in the design and development of most forms of RF communication devices and networks. Towards the objective of achieving RF jamming through the use of DSA enabled cognitive radio swarms; a distributed network of CR devices acting autonomously to form a MANET is introduced. Current efforts to standardize next generation Cognitive Radio technology and advanced spectrum management have introduced a policy language and architecture for controlling and regulating the behavior of such devices. For the purposes of this system, SDR is a medium towards CR devices that are controlled through well-defined policies that support DSA.

Policies use a machine-interpretable language to specify authorized frequencies, transmission power levels, channel designation, time periods, geospatial settings, and other specific spectrum access requirements (Perich, 2007). The CR policy reasoner and CR policy enforcer, illustrated in Figure 1, ensure that the constraints implied by policy restrictions are adhered to. With the standardization of the policy language and establishment of CR policy architecture, the generation and dissemination of policies as well as the implied adherence and enforcement of said policies on CR devices can be automated (Perich, Foster, Tenhula, & McHenry, 2008). The implication of this automation is that a device component with capabilities to generate and disseminate policies supersedes that of a single CR device.

Figure 1.

IEEE cognitive radio policy control system architecture

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