203 research outputs found
Optimal and Robust Transmit Designs for MISO Channel Secrecy by Semidefinite Programming
In recent years there has been growing interest in study of multi-antenna
transmit designs for providing secure communication over the physical layer.
This paper considers the scenario of an intended multi-input single-output
channel overheard by multiple multi-antenna eavesdroppers. Specifically, we
address the transmit covariance optimization for secrecy-rate maximization
(SRM) of that scenario. The challenge of this problem is that it is a nonconvex
optimization problem. This paper shows that the SRM problem can actually be
solved in a convex and tractable fashion, by recasting the SRM problem as a
semidefinite program (SDP). The SRM problem we solve is under the premise of
perfect channel state information (CSI). This paper also deals with the
imperfect CSI case. We consider a worst-case robust SRM formulation under
spherical CSI uncertainties, and we develop an optimal solution to it, again
via SDP. Moreover, our analysis reveals that transmit beamforming is generally
the optimal transmit strategy for SRM of the considered scenario, for both the
perfect and imperfect CSI cases. Simulation results are provided to illustrate
the secrecy-rate performance gains of the proposed SDP solutions compared to
some suboptimal transmit designs.Comment: 32 pages, 5 figures; to appear, IEEE Transactions on Signal
Processing, 201
Spatially Selective Artificial-Noise Aided Transmit Optimization for MISO Multi-Eves Secrecy Rate Maximization
Consider an MISO channel overheard by multiple eavesdroppers. Our goal is to
design an artificial noise (AN)-aided transmit strategy, such that the
achievable secrecy rate is maximized subject to the sum power constraint.
AN-aided secure transmission has recently been found to be a promising approach
for blocking eavesdropping attempts. In many existing studies, the confidential
information transmit covariance and the AN covariance are not simultaneously
optimized. In particular, for design convenience, it is common to prefix the AN
covariance as a specific kind of spatially isotropic covariance. This paper
considers joint optimization of the transmit and AN covariances for secrecy
rate maximization (SRM), with a design flexibility that the AN can take any
spatial pattern. Hence, the proposed design has potential in jamming the
eavesdroppers more effectively, based upon the channel state information (CSI).
We derive an optimization approach to the SRM problem through both analysis and
convex conic optimization machinery. We show that the SRM problem can be recast
as a single-variable optimization problem, and that resultant problem can be
efficiently handled by solving a sequence of semidefinite programs. Our
framework deals with a general setup of multiple multi-antenna eavesdroppers,
and can cater for additional constraints arising from specific application
scenarios, such as interference temperature constraints in interference
networks. We also generalize the framework to an imperfect CSI case where a
worst-case robust SRM formulation is considered. A suboptimal but safe solution
to the outage-constrained robust SRM design is also investigated. Simulation
results show that the proposed AN-aided SRM design yields significant secrecy
rate gains over an optimal no-AN design and the isotropic AN design, especially
when there are more eavesdroppers.Comment: To appear in IEEE Trans. Signal Process., 201
Robust Secure Transmission in MISO Channels Based on Worst-Case Optimization
This paper studies robust transmission schemes for multiple-input
single-output (MISO) wiretap channels. Both the cases of direct transmission
and cooperative jamming with a helper are investigated with imperfect channel
state information (CSI) for the eavesdropper links. Robust transmit covariance
matrices are obtained based on worst-case secrecy rate maximization, under both
individual and global power constraints. For the case of an individual power
constraint, we show that the non-convex maximin optimization problem can be
transformed into a quasiconvex problem that can be efficiently solved with
existing methods. For a global power constraint, the joint optimization of the
transmit covariance matrices and power allocation between the source and the
helper is studied via geometric programming. We also study the robust wiretap
transmission problem for the case with a quality-of-service constraint at the
legitimate receiver. Numerical results show the advantage of the proposed
robust design. In particular, for the global power constraint scenario,
although cooperative jamming is not necessary for optimal transmission with
perfect eavesdropper's CSI, we show that robust jamming support can increase
the worst-case secrecy rate and lower the signal to interference-plus-noise
ratio at Eve in the presence of channel mismatches between the transmitters and
the eavesdropper.Comment: 28 pages, 5 figure
Beamforming Techniques for Non-Orthogonal Multiple Access in 5G Cellular Networks
In this paper, we develop various beamforming techniques for downlink
transmission for multiple-input single-output (MISO) non-orthogonal multiple
access (NOMA) systems. First, a beamforming approach with perfect channel state
information (CSI) is investigated to provide the required quality of service
(QoS) for all users. Taylor series approximation and semidefinite relaxation
(SDR) techniques are employed to reformulate the original non-convex power
minimization problem to a tractable one. Further, a fairness-based beamforming
approach is proposed through a max-min formulation to maintain fairness between
users. Next, we consider a robust scheme by incorporating channel
uncertainties, where the transmit power is minimized while satisfying the
outage probability requirement at each user. Through exploiting the SDR
approach, the original non-convex problem is reformulated in a linear matrix
inequality (LMI) form to obtain the optimal solution. Numerical results
demonstrate that the robust scheme can achieve better performance compared to
the non-robust scheme in terms of the rate satisfaction ratio. Further,
simulation results confirm that NOMA consumes a little over half transmit power
needed by OMA for the same data rate requirements. Hence, NOMA has the
potential to significantly improve the system performance in terms of transmit
power consumption in future 5G networks and beyond.Comment: accepted to publish in IEEE Transactions on Vehicular Technolog
Outage Constrained Robust Secure Transmission for MISO Wiretap Channels
In this paper we consider the robust secure beamformer design for MISO
wiretap channels. Assume that the eavesdroppers' channels are only partially
available at the transmitter, we seek to maximize the secrecy rate under the
transmit power and secrecy rate outage probability constraint. The outage
probability constraint requires that the secrecy rate exceeds certain threshold
with high probability. Therefore including such constraint in the design
naturally ensures the desired robustness. Unfortunately, the presence of the
probabilistic constraints makes the problem non-convex and hence difficult to
solve. In this paper, we investigate the outage probability constrained secrecy
rate maximization problem using a novel two-step approach. Under a wide range
of uncertainty models, our developed algorithms can obtain high-quality
solutions, sometimes even exact global solutions, for the robust secure
beamformer design problem. Simulation results are presented to verify the
effectiveness and robustness of the proposed algorithms
Secrecy Wireless Information and Power Transfer with MISO Beamforming
The dual use of radio signals for simultaneous wireless information and power
transfer (SWIPT) has recently drawn significant attention. To meet the
practical requirement that energy receivers (ERs) operate with significantly
higher received power as compared to information receivers (IRs), ERs need to
be deployed in more proximity to the transmitter than IRs. However, due to the
broadcast nature of wireless channels, one critical issue arises that the
messages sent to IRs can be eavesdropped by ERs, which possess better channels
from the transmitter. In this paper, we address this new secrecy communication
problem in a multiuser multiple-input single-output (MISO) SWIPT system where
one multi-antenna transmitter sends information and energy simultaneously to an
IR and multiple ERs, each with one single antenna. To optimally design transmit
beamforming vectors and their power allocation, two problems are investigated
with different aims: the first problem maximizes the secrecy rate for IR
subject to individual harvested energy constraints of ERs, while the second
problem maximizes the weighted sum-energy transferred to ERs subject to a
secrecy rate constraint for IR. We solve these two non-convex problems
optimally by reformulating each of them into a two-stage problem. First, by
fixing the signal-to-interference-plus-noise ratio (SINR) target for ERs (for
the first problem) or IR (for the second problem), we obtain the optimal
beamforming and power allocation solution by applying the technique of
semidefinite relaxation (SDR). Then, the original problems are solved by a
one-dimension search over the optimal SINR target for ERs or IR. Furthermore,
for each of the two studied problems, suboptimal solutions of lower complexity
are also proposed in which the information and energy beamforming vectors are
separately designed with their power allocation.Comment: accepted by IEEE Transactions on Signal Processing. Longer version of
arXiv:1306.096
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