Random, Persistent, and Adaptive Spectrum Sensing Strategies for Multiband Spectrum Sensing in Cognitive Radio Networks With Secondary User Hardware Limitation

Abstract

In this paper, we consider hardware limitation at the secondary user, which makes multiband (wideband) spectrum sensing more challenging. Under secondary user (SU) hardware limitation, the SU can only sense a small portion of the multiband spectrum for a given time period, which introduces a design issue of selecting subchannels to sense at a given time. A random spectrum sensing strategy (RSSS) is presented to select the subchannels to sense in a totally random fashion. With the Markov assumption of the primary user (PU) behavior, a persistent spectrum sensing strategy (PSSS) is proposed to take advantage of the PU traffic patterns in determining the channels to sense. Theoretical and simulation results show that RSSS and PSSS display different performance in different ranges of PU traffic parameters. We finally propose an adaptive spectrum sensing strategy (ASSS), which determines whether to use RSSS or PSSS for spectrum sensing at a given time based on the estimated PU traffic parameters. Numerical results under various system parameters are presented to evaluate the performance of RSSS, PSSS, and ASSS. The ASSS is shown to gain the advantages of both RSSS and PSSS in different ranges of PU traffic parameters and provide more available subchannels for SU.

Keywords

• Adaptive spectrum sensing
• cognitive radio
• subchannel selection
• wideband spectrum sensing
• Markov model