TY - GEN
T1 - Blind null-space tracking for MIMO underlay cognitive radio networks
AU - Manolakos, Alexandros
AU - Noam, Yair
AU - Dimou, Konstantinos
AU - Goldsmith, Andrea J.
PY - 2012
Y1 - 2012
N2 - Blind Null Space Learning [1] has recently been proposed for fast and accurate learning of the null-space associated with the channel matrix between a secondary transmitter and a primary receiver. In this paper we propose a channel tracking enhancement of the algorithm, namely the Blind Null Space Tracking algorithm, that allows transmission of information to the Secondary Receiver while simultaneously learning the null-space of the time-varying target channel. Specifically, the enhanced algorithm initially performs a sweep in order to acquire the null space. Then, it performs modified Jacobi rotations such that the induced interference is kept lower than a given threshold P Th with probability p while information is transmitted to the secondary receiver simultaneously. The learning process is performed based on sensing whether the transmit power of the primary user has increased or decreased between adaptations. We present simulation results indicating that the proposed approach has strictly better performance over the Blind Null Space Learning algorithm for channels with independent Rayleigh fading at a low Doppler frequency.
AB - Blind Null Space Learning [1] has recently been proposed for fast and accurate learning of the null-space associated with the channel matrix between a secondary transmitter and a primary receiver. In this paper we propose a channel tracking enhancement of the algorithm, namely the Blind Null Space Tracking algorithm, that allows transmission of information to the Secondary Receiver while simultaneously learning the null-space of the time-varying target channel. Specifically, the enhanced algorithm initially performs a sweep in order to acquire the null space. Then, it performs modified Jacobi rotations such that the induced interference is kept lower than a given threshold P Th with probability p while information is transmitted to the secondary receiver simultaneously. The learning process is performed based on sensing whether the transmit power of the primary user has increased or decreased between adaptations. We present simulation results indicating that the proposed approach has strictly better performance over the Blind Null Space Learning algorithm for channels with independent Rayleigh fading at a low Doppler frequency.
UR - http://www.scopus.com/inward/record.url?scp=84877661929&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877661929&partnerID=8YFLogxK
U2 - 10.1109/GLOCOM.2012.6503280
DO - 10.1109/GLOCOM.2012.6503280
M3 - Conference contribution
AN - SCOPUS:84877661929
SN - 9781467309219
T3 - Proceedings - IEEE Global Communications Conference, GLOBECOM
SP - 1223
EP - 1229
BT - 2012 IEEE Global Communications Conference, GLOBECOM 2012
T2 - 2012 IEEE Global Communications Conference, GLOBECOM 2012
Y2 - 3 December 2012 through 7 December 2012
ER -