TY - GEN
T1 - Ergodic capacity analysis in cognitive radio systems under channel uncertainty
AU - Akin, Sami
AU - Gursoy, Mustafa Cenk
N1 - Copyright:
Copyright 2010 Elsevier B.V., All rights reserved.
PY - 2010
Y1 - 2010
N2 - In this paper, pilot-symbol-assisted transmission in cognitive radio systems over time selective flat fading channels is studied. It is assumed that causal and non causal Wiener filter estimators are used at the secondary receiver with the aid of training symbols to obtain the channel side information (CSI) under an interference power constraint. Cognitive radio model is described together with detection and false alarm probabilities determined by using a Neyman-Person detector for channel sensing. Subsequently, for both filters, the variances of estimate errors are calculated from the Doppler power spectrum of the channel, and achievable rate expressions are provided considering the scenarios which are results of channel sensing. Numerical results are obtained in Gauss-Markov modeled channels, and achievable rates obtained by using causal and non causal filters are compared and it is shown that the difference is decreasing with increasing signal-to-noise ratio (SNR). Moreover, the optimal probability of detection and false alarm values are shown, and the tradeoff between these two parameters is discussed. Finally, optimal power distributions are provided.
AB - In this paper, pilot-symbol-assisted transmission in cognitive radio systems over time selective flat fading channels is studied. It is assumed that causal and non causal Wiener filter estimators are used at the secondary receiver with the aid of training symbols to obtain the channel side information (CSI) under an interference power constraint. Cognitive radio model is described together with detection and false alarm probabilities determined by using a Neyman-Person detector for channel sensing. Subsequently, for both filters, the variances of estimate errors are calculated from the Doppler power spectrum of the channel, and achievable rate expressions are provided considering the scenarios which are results of channel sensing. Numerical results are obtained in Gauss-Markov modeled channels, and achievable rates obtained by using causal and non causal filters are compared and it is shown that the difference is decreasing with increasing signal-to-noise ratio (SNR). Moreover, the optimal probability of detection and false alarm values are shown, and the tradeoff between these two parameters is discussed. Finally, optimal power distributions are provided.
UR - http://www.scopus.com/inward/record.url?scp=77953705606&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77953705606&partnerID=8YFLogxK
U2 - 10.1109/CISS.2010.5464753
DO - 10.1109/CISS.2010.5464753
M3 - Conference contribution
AN - SCOPUS:77953705606
SN - 9781424474172
T3 - 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010
BT - 2010 44th Annual Conference on Information Sciences and Systems, CISS 2010
T2 - 44th Annual Conference on Information Sciences and Systems, CISS 2010
Y2 - 17 March 2010 through 19 March 2010
ER -