A Novel Low Complexity High Resolution Spectrum Hole Detection Technique for Cognitive Radio

TL;DR

This paper introduces a low complexity, high resolution spectrum hole detection method for cognitive radio using a two-stage filtering approach that efficiently identifies spectrum holes without increasing hardware complexity.

Contribution

It proposes a novel two-stage frequency response masking filter technique combined with Pascal structure sampling rate converters for high-resolution spectrum sensing.

Findings

Achieves high-resolution spectrum hole detection with low hardware complexity.

Outperforms existing methods in hardware efficiency.

Effective in detecting even small spectrum holes.

Abstract

Cognitive radio is a potential solution to meet the upcoming spectrum crunch issue. In a cognitive radio, spectrum holes can be identified using spectrum sensing techniques. A high resolution spectrum hole detection can ensure even the smallest inactive portion in the spectrum is efficiently utilized. In this paper, a spectrum hole detection technique is proposed in which coarse sensing is done initially so as to detect occupied channels simultaneously. Spectrum holes in the occupied band can be efficiently detected using a fine sensing method. A two stage Frequency Response Masking (FRM) filter sandwiched between two Pascal structure based sampling rate converters results in arbitrary variation of bandwidth. This arbitrary variation of bandwidth can be utilized for fine sensing the spectrum such that the spectrum holes can be detected with high resolution. In the proposed method, high resolution in spectrum hole detection can be achieved without increasing the hardware complexity of the design. The hardware complexity of the proposed method is compared with the state of the art and is found to be significantly less