Signal & System Theory Group

Mr. Aaron Pries

Research Associate

M.Sc. (Universität Paderborn), 2015

Room: P1.7.13.1
Phone: +49 (0)5251 60-2429
[javascript protected email address]




Mr. Pries joined the SST group in October 2015.

List of Publications

1

Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio
(Aaron Pries, David Ramírez and Peter J. Schreier)
Proc. IEEE Int. Conf. Acoustics, Speech and Signal Process.,  pp. 4249–4253, Shanghai, China, March 2016.
DOI:10.1109/ICASSP.2016.7472478.
[BibTeX]
@inproceedings{pries2016,
abstract = {One approach to spectrum sensing for cognitive radio is the detection of cyclostationarity. We extend an existing multi-antenna detector for cyclostationarity proposed by Ram{\'i}rez et al. [1], which makes no assumptions about the noise beyond being (temporally) wide-sense stationary. In special cases, the noise could be uncorrelated among antennas, or it could be temporally white. The performance of a general detector can be improved by making use of a priori structural information. We do not, however, require knowledge of the exact values of the temporal or spatial noise covariances. We develop an asymptotic generalized likelihood ratio test and evaluate the performance by simulations.},
author = {Aaron Pries and David Ram{\'i}rez and Peter J. Schreier},
booktitle = {{P}roc.\ {IEEE} {I}nt.\ {C}onf.\ {A}coustics, {S}peech and {S}ignal {P}rocess.},
title = {Detection of cyclostationarity in the presence of temporal or spatial structure with applications to cognitive radio},
year = {2016},
pages = {4249–4253},
month = {{M}arch},
address = {Shanghai, China},
doi = {10.1109/ICASSP.2016.7472478},
}
[Abstract]
One approach to spectrum sensing for cognitive radio is the detection of cyclostationarity. We extend an existing multi-antenna detector for cyclostationarity proposed by Ramírez et al. [1], which makes no assumptions about the noise beyond being (temporally) wide-sense stationary. In special cases, the noise could be uncorrelated among antennas, or it could be temporally white. The performance of a general detector can be improved by making use of a priori structural information. We do not, however, require knowledge of the exact values of the temporal or spatial noise covariances. We develop an asymptotic generalized likelihood ratio test and evaluate the performance by simulations.