Spectrum Sensing in Wideband OFDM Cognitive Radios

In this paper, spectrum sensing of an orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) is addressed. The goal is to identify the portions of the spectrum that are unused by primary user systems and other CR systems, called existing user (EU) systems altogether, with the e...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on signal processing 2010-02, Vol.58 (2), p.709-719
Main Authors: Hwang, Chien-Hwa, Lai, Guan-Long, Chen, Shih-Chang
Format: Article
Language:English
Subjects:
Autoregressive model
Channels
Chromium
Cognitive radio
cognitive radio (CR)
Detection
dynamic programming
Fading
Frequency estimation
Frequency measurement
Maximum likelihood detection
Maximum likelihood estimation
OFDM
Orthogonal Frequency Division Multiplexing
orthogonal frequency division multiplexing (OFDM)
Radio
Radiofrequency identification
Segments
spectrum sensing
Subcarriers
Wideband
Wireless networks
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:In this paper, spectrum sensing of an orthogonal frequency division multiplexing (OFDM) based cognitive radio (CR) is addressed. The goal is to identify the portions of the spectrum that are unused by primary user systems and other CR systems, called existing user (EU) systems altogether, with the emphasis on conquering the challenge imposed by multipath fading channel. The sensing of EU systems consists of two steps. In the first step, the maximum likelihood (ML) estimates of the frequency bands of EU systems are calculated; in the second step, detection is performed at each suspected band to decide whether an EU system is truly in operation. The idea is that an EU system appears at a segment of continuous subcarriers. This fact can be exploited by employing measurements at a continual subcarriers and executing the sensing along the frequency domain. An autoregressive (AR) model is adopted to track the variation of the received EU signal strength along frequencies. It is shown by simulations that the proposed spectrum sensing algorithm is robust in a severe frequency-selective fading channel.
ISSN:1053-587X
1941-0476
DOI:10.1109/TSP.2009.2032453