Detecting the presence of primary users and ability to find white spaces in the spectrum are the key enablers of the opportunistic communication. This paper analyzes the trade-offs in cyclostationary-based spectrum sensing algorithm implementations in terms of performance, hardware complexity, and power consumption. The evaluation of the algorithm implementations is performed on field-programmable gate arrays. The analysis presented will provide the designer understanding of dependency between algorithm complexity and power consumption, which is inherently limiting factor of implementation feasibility for cognitive mobile devices.
Emerging wireless systems demand more spectrum in order to provide high data rate services. It is known that most of the licensed frequency bands are underutilized because of the rigid spectrum allocation. Cognitive radios aim to relief the situation by identifying and exploiting the underutilized radio spectrum. A key task of the cognitive radio is spectrum sensing, which finds free spectrum and detects licensed spectrum user transmissions. This paper presents an FPGA implementation of an autocorrelation-based feature detector for OFDM-based primary user signals. The autocorrelationbased detection algorithm is optimized in order to achieve power and area efficient hardware realization. The algorithm is implemented in an FPGA evaluation environment, and the performance is verified with measurements.
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