A Novel Hardware Efficient High Resolution Spectrum Hole Detection Technique for Cognitive Radio

Abstract

ABSTRACT Cognitive radio is a potential solution to meet the upcoming spectrum scarcity issue. Spectrum sensing techniques can be employed in a cognitive radio. Even the smallest inactive section of the spectrum can be effectively used with high-resolution spectrum hole detection. This study proposes a method for detecting spectrum holes that performs coarse sensing as a first stage for finding occupied channels simultaneously. A fine sensing technique is proposed as a second stage using which we can efficiently find spectrum holes in the occupied band. A two-stage Frequency Response Masking (FRM) filter sandwiched between two Pascal structure based sampling rate converters results in arbitrary variation of bandwidth. By using this arbitrary variation in bandwidth, it is possible to identify spectrum holes with high resolution while fine sensing the spectrum. High-resolution spectrum hole detection can be accomplished using the proposed technique without adding to the hardware design’s complexity. When the proposed method’s hardware complexity is compared to the state of the art, it is observed to be substantially reduced. The prototype filter used for spectrum hole detection is synthesised using Xilinx Vivado and Cadence Genus tool for the area and power analysis.