TY - JOUR
T1 - MMSE-SLNR precoding for multi-antenna cognitive radio
AU - Richter, Yiftach
AU - Bergel, Itsik
PY - 2014/5/15
Y1 - 2014/5/15
N2 - In this paper, we propose and optimize a low-complexity precoding scheme for multiple antenna cognitive radio networks. In a cognitive network, a secondary transmitter is allowed to access the spectrum of the primary network only if the interference to the primary network remains below the predefined power limit. The proposed scheme, termed MSLNR, is a combination of the optimal minimum-mean-square-error (MMSE) receiver and the signal-to-leakage-plus-noise- ratio (SLNR) transmitter, with additional scaling to comply with the cognitive interference constraint. We also present a robust design method for the case where the secondary transmitter has only partial channel state information (CSI). The MSLNR scheme requires low implementation complexity. The transmit precoder is evaluated while taking into account the optimal receiver weight, but without any iterations. Yet, simulation results demonstrate that the performance of the proposed MSLNR scheme is close to the performance of the best known solution.
AB - In this paper, we propose and optimize a low-complexity precoding scheme for multiple antenna cognitive radio networks. In a cognitive network, a secondary transmitter is allowed to access the spectrum of the primary network only if the interference to the primary network remains below the predefined power limit. The proposed scheme, termed MSLNR, is a combination of the optimal minimum-mean-square-error (MMSE) receiver and the signal-to-leakage-plus-noise- ratio (SLNR) transmitter, with additional scaling to comply with the cognitive interference constraint. We also present a robust design method for the case where the secondary transmitter has only partial channel state information (CSI). The MSLNR scheme requires low implementation complexity. The transmit precoder is evaluated while taking into account the optimal receiver weight, but without any iterations. Yet, simulation results demonstrate that the performance of the proposed MSLNR scheme is close to the performance of the best known solution.
KW - Cognitive radio
KW - poisson point process
KW - wireless ad hoc networks
UR - http://www.scopus.com/inward/record.url?scp=84900000976&partnerID=8YFLogxK
U2 - 10.1109/tsp.2014.2314442
DO - 10.1109/tsp.2014.2314442
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AN - SCOPUS:84900000976
SN - 1053-587X
VL - 62
SP - 2719
EP - 2729
JO - IEEE Transactions on Signal Processing
JF - IEEE Transactions on Signal Processing
IS - 10
M1 - 6781048
ER -