7 research outputs found
Two-Way Training for Discriminatory Channel Estimation in Wireless MIMO Systems
This work examines the use of two-way training to efficiently discriminate
the channel estimation performances at a legitimate receiver (LR) and an
unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless
system. This work improves upon the original discriminatory channel estimation
(DCE) scheme proposed by Chang et al where multiple stages of feedback and
retraining were used. While most studies on physical layer secrecy are under
the information-theoretic framework and focus directly on the data transmission
phase, studies on DCE focus on the training phase and aim to provide a
practical signal processing technique to discriminate between the channel
estimation performances at LR and UR. A key feature of DCE designs is the
insertion of artificial noise (AN) in the training signal to degrade the
channel estimation performance at UR. To do so, AN must be placed in a
carefully chosen subspace based on the transmitter's knowledge of LR's channel
in order to minimize its effect on LR. In this paper, we adopt the idea of
two-way training that allows both the transmitter and LR to send training
signals to facilitate channel estimation at both ends. Both reciprocal and
non-reciprocal channels are considered and a two-way DCE scheme is proposed for
each scenario. {For mathematical tractability, we assume that all terminals
employ the linear minimum mean square error criterion for channel estimation.
Based on the mean square error (MSE) of the channel estimates at all
terminals,} we formulate and solve an optimization problem where the optimal
power allocation between the training signal and AN is found by minimizing the
MSE of LR's channel estimate subject to a constraint on the MSE achievable at
UR. Numerical results show that the proposed DCE schemes can effectively
discriminate between the channel estimation and hence the data detection
performances at LR and UR.Comment: 1
Two-way training for discriminatory channel estimation in wireless MIMO systems
This work examines the use of two-way training to efficiently discriminate the channel estimation performances at a legitimate receiver (LR) and an unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless system. This work improves upon the original discriminatory channel estimation (DCE) scheme proposed by Chang where multiple stages of feedback and retraining were used. While most studies on physical layer secrecy are under the information-theoretic framework and focus directly on the data transmission phase, studies on DCE focus on the training phase and aim to provide a practical signal processing technique to discriminate between the channel estimation performances (and, thus, the effective received signal qualities) at LR and UR. A key feature of DCE designs is the insertion of artificial noise (AN) in the training signal to degrade the channel estimation performance at UR. To do so, AN must be placed in a carefully chosen subspace, based on the transmitter's knowledge of LR's channel, in order to minimize its effect on LR. In this paper, we adopt the idea of two-way training that allows both the transmitter and LR to send training signals to facilitate channel estimation at both ends. Both reciprocal and nonreciprocal channels are considered and a two-way DCE scheme is proposed for each scenario. For mathematical tractability, we assume that all terminals employ the linear minimum mean square error criterion for channel estimation. Based on the mean square error (MSE) of the channel estimates at all terminals, we formulate and solve an optimization problem where the optimal power allocation between the training signal and AN is found by minimizing the MSE of LR's channel estimate subject to a constraint on the MSE achievable at UR. Numerical results show that the proposed DCE schemes can effectively discriminate between the channel estimation and, hence, the data detection performances at LR and UR.This work was supported in part by the National Science Council, Taiwan, by Grant NSC 100-2628-E-007-025-MY3 and Grant NSC 101-2218-E-011-043, and in part by the Australian Research Council's Discovery Projects Funding Scheme (Project no.DP110102548)
A Semiblind Two-Way Training Method for Discriminatory Channel Estimation in MIMO Systems
Discriminatory channel estimation (DCE) is a recently developed strategy to
enlarge the performance difference between a legitimate receiver (LR) and an
unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless
system. Specifically, it makes use of properly designed training signals to
degrade channel estimation at the UR which in turn limits the UR's
eavesdropping capability during data transmission. In this paper, we propose a
new two-way training scheme for DCE through exploiting a whitening-rotation
(WR) based semiblind method. To characterize the performance of DCE, a
closed-form expression of the normalized mean squared error (NMSE) of the
channel estimation is derived for both the LR and the UR. Furthermore, the
developed analytical results on NMSE are utilized to perform optimal power
allocation between the training signal and artificial noise (AN). The
advantages of our proposed DCE scheme are two folds: 1) compared to the
existing DCE scheme based on the linear minimum mean square error (LMMSE)
channel estimator, the proposed scheme adopts a semiblind approach and achieves
better DCE performance; 2) the proposed scheme is robust against active
eavesdropping with the pilot contamination attack, whereas the existing scheme
fails under such an attack.Comment: accepted for publication in IEEE Transactions on Communication
Secret Channel Training to Enhance Physical Layer Security With a Full-Duplex Receiver
This work proposes a new channel training (CT)
scheme for a full-duplex receiver to enhance physical layer
security. Equipped with NB full-duplex antennas, the receiver
simultaneously receives the information signal and transmits
artificial noise (AN). In order to reduce the non-cancellable
self-interference due to the transmitted AN, the receiver has
to estimate the self-interference channel prior to the data
communication phase. In the proposed CT scheme, the receiver
transmits a limited number of pilot symbols which are known
only to itself. Such a secret CT scheme prevents an eavesdropper
from estimating the jamming channel from the receiver to
the eavesdropper, hence effectively degrading the eavesdropping
capability. We analytically examine the connection probability
(i.e., the probability of the data being successfully decoded by the
receiver) of the legitimate channel and the secrecy outage probability
due to eavesdropping for the proposed secret CT scheme.
Based on our analysis, the optimal power allocation between CT
and data/AN transmission at the legitimate transmitter/receiver
is determined. Our examination shows that the newly proposed
secret CT scheme significantly outperforms the non-secret CT
scheme that uses publicly known pilots when the number of
antennas at the eavesdropper is larger than one.ARC Discovery Projects Grant DP15010390
Optimal Pilots for Anti-Eavesdropping Channel Estimation
Anti-eavesdropping channel estimation (ANECE) is a method that uses specially
designed pilot signals to allow two or more full-duplex radio devices each with
one or more antennas to estimate their channel state information (CSI)
consistently and at the same time prevent eavesdropper (Eve) with any number of
antennas from obtaining its CSI consistently. This paper presents optimal
designs of the pilots for ANECE based on two criteria. The first is the mean
squared error (MSE) of channel estimation for the users, and the second is the
mutual information (MI) between the pilot-driven signals observed by the users.
Closed-form optimal pilots are shown under the sum-MSE and sum-MI criteria
subject to a symmetric and isotropic condition. Algorithms for computing the
optimal pilots are shown for general cases. Fairness issues for three or more
users are discussed. The performances of different designs are compared
Principles of Physical Layer Security in Multiuser Wireless Networks: A Survey
This paper provides a comprehensive review of the domain of physical layer
security in multiuser wireless networks. The essential premise of
physical-layer security is to enable the exchange of confidential messages over
a wireless medium in the presence of unauthorized eavesdroppers without relying
on higher-layer encryption. This can be achieved primarily in two ways: without
the need for a secret key by intelligently designing transmit coding
strategies, or by exploiting the wireless communication medium to develop
secret keys over public channels. The survey begins with an overview of the
foundations dating back to the pioneering work of Shannon and Wyner on
information-theoretic security. We then describe the evolution of secure
transmission strategies from point-to-point channels to multiple-antenna
systems, followed by generalizations to multiuser broadcast, multiple-access,
interference, and relay networks. Secret-key generation and establishment
protocols based on physical layer mechanisms are subsequently covered.
Approaches for secrecy based on channel coding design are then examined, along
with a description of inter-disciplinary approaches based on game theory and
stochastic geometry. The associated problem of physical-layer message
authentication is also introduced briefly. The survey concludes with
observations on potential research directions in this area.Comment: 23 pages, 10 figures, 303 refs. arXiv admin note: text overlap with
arXiv:1303.1609 by other authors. IEEE Communications Surveys and Tutorials,
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