Signal Classification in Fading Channels Using Cyclic Spectral Analysis
Abstract
Cognitive Radio (CR), a hierarchical Dynamic Spectrum Access (DSA) model, has been considered as a strong candidate for future communication systems improving spectrum efficiency utilizing unused spectrum of opportunity. However to ensure the effectiveness of dynamic spectrum access, accurate signal classification in fading channels at low signal to noise ratio is essential. In this paper, a hierarchical cyclostationary-based classifier is proposed to reliably identify the signal type of a wide range of unknown signals. The proposed system assumes no a priori knowledge of critical signal statistics such as carrier frequency, carrier phase, or symbol rate. The system is designed with a multistate approach to minimize the number of samples required to make a classification decision while simultaneously ensuring the greatest reliability in the current and previous stages. The system performance is demonstrated in a variety of multipath fading channels, where several multiantenna-based combining schemes are implemented to exploit spatial diversity.
Document Details
- Document Type
- Technical Report
- Publication Date
- Jul 01, 2009
- Accession Number
- ADA516557
Entities
People
- E. P. Ratazzi
- Eric Like
- Vasu D. Chakravarthy
- Zhiqiang Wu
Organizations
- Air Force Institute of Technology