TY - GEN
T1 - An improved two-way training for discriminatory channel estimation via semiblind approach
AU - Yang, Junjie
AU - Yu, Rong
AU - Zhou, Xiangyun
AU - Zhang, Yan
PY - 2014
Y1 - 2014
N2 - This paper studies the discriminatory channel estimation (DCE) performance between a legitimate receiver (LR) and an unauthorized receiver (UR) in the multiple-input multiple-output (MIMO) wireless systems. DCE is a recently developed concept that intentionally degrades the channel estimation at the UR so as to minimize the probability of confidential information being eavesdropped by the UR. Usually, the existing DCE scheme is based on the linear minimum mean square error (LMMSE) method with two-way training. In this paper, we propose a new two-way training for DCE based on semiblind approach, e.g., the whitening-rotation (WR)-based channel estimator. To characterize the DCE performance, we derive the closed-form of the normalized mean squared error (NMSE) to the channel estimation at both the LR and the UR. Simulation results show that the proposed two-way training achieves higher performance compared to the two-way training designs in the literature.
AB - This paper studies the discriminatory channel estimation (DCE) performance between a legitimate receiver (LR) and an unauthorized receiver (UR) in the multiple-input multiple-output (MIMO) wireless systems. DCE is a recently developed concept that intentionally degrades the channel estimation at the UR so as to minimize the probability of confidential information being eavesdropped by the UR. Usually, the existing DCE scheme is based on the linear minimum mean square error (LMMSE) method with two-way training. In this paper, we propose a new two-way training for DCE based on semiblind approach, e.g., the whitening-rotation (WR)-based channel estimator. To characterize the DCE performance, we derive the closed-form of the normalized mean squared error (NMSE) to the channel estimation at both the LR and the UR. Simulation results show that the proposed two-way training achieves higher performance compared to the two-way training designs in the literature.
KW - Discriminatory channel estimation
KW - Physical layer security
KW - semiblind approach
UR - http://www.scopus.com/inward/record.url?scp=84906998208&partnerID=8YFLogxK
U2 - 10.1109/ICC.2014.6884020
DO - 10.1109/ICC.2014.6884020
M3 - Conference contribution
SN - 9781479920037
T3 - 2014 IEEE International Conference on Communications, ICC 2014
SP - 4442
EP - 4447
BT - 2014 IEEE International Conference on Communications, ICC 2014
PB - IEEE Computer Society
T2 - 2014 1st IEEE International Conference on Communications, ICC 2014
Y2 - 10 June 2014 through 14 June 2014
ER -