Computer Science – Information Theory
Scientific paper
2010-05-09
Computer Science
Information Theory
24 pages
Scientific paper
This paper considers the problem of spectrum sensing in cognitive radio networks when the primary user employs Orthogonal Frequency Division Multiplexing (OFDM). We develop cooperative sequential detection algorithms based on energy detectors and the autocorrelation property of cyclic prefix (CP) used in OFDM systems and compare their performances. We show that sequential detection provides much better performance than the traditional fixed sample size (snapshot) based detectors. We also study the effect of model uncertainties such as timing and frequency offset, IQ-imbalance and uncertainty in noise and transmit power on the performance of the detectors. We modify the detectors to mitigate the effects of these impairments. The performance of the proposed algorithms are studied via simulations. It is shown that energy detector performs significantly better than the CP-based detector, except in case of a snapshot detector with noise power uncertainty. Also, unlike for the CP-based detector, most of the above mentioned impairments have no effect on the energy detector.
Jayaprakasam ArunKumar
Murthy Chandra R.
Narayanan Prashant
Sharma Vinod
No associations
LandOfFree
Cooperative Sequential Spectrum Sensing Algorithms for OFDM does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Cooperative Sequential Spectrum Sensing Algorithms for OFDM, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Cooperative Sequential Spectrum Sensing Algorithms for OFDM will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-611847