423 research outputs found
Secure Beamforming For MIMO Broadcasting With Wireless Information And Power Transfer
This paper considers a basic MIMO information-energy (I-E) broadcast system,
where a multi-antenna transmitter transmits information and energy
simultaneously to a multi-antenna information receiver and a dual-functional
multi-antenna energy receiver which is also capable of decoding information.
Due to the open nature of wireless medium and the dual purpose of information
and energy transmission, secure information transmission while ensuring
efficient energy harvesting is a critical issue for such a broadcast system.
Assuming that physical layer security techniques are applied to the system to
ensure secure transmission from the transmitter to the information receiver, we
study beamforming design to maximize the achievable secrecy rate subject to a
total power constraint and an energy harvesting constraint. First, based on
semidefinite relaxation, we propose global optimal solutions to the secrecy
rate maximization (SRM) problem in the single-stream case and a specific
full-stream case where the difference of Gram matrices of the channel matrices
is positive semidefinite. Then, we propose a simple iterative algorithm named
inexact block coordinate descent (IBCD) algorithm to tackle the SRM problem of
general case with arbitrary number of streams. We proves that the IBCD
algorithm can monotonically converge to a Karush-Kuhn-Tucker (KKT) solution to
the SRM problem. Furthermore, we extend the IBCD algorithm to the joint
beamforming and artificial noise design problem. Finally, simulations are
performed to validate the performance of the proposed beamforming algorithms.Comment: Submitted to journal for possible publication. First submission to
arXiv Mar. 14 201
Joint Unitary Triangularization for MIMO Networks
This work considers communication networks where individual links can be
described as MIMO channels. Unlike orthogonal modulation methods (such as the
singular-value decomposition), we allow interference between sub-channels,
which can be removed by the receivers via successive cancellation. The degrees
of freedom earned by this relaxation are used for obtaining a basis which is
simultaneously good for more than one link. Specifically, we derive necessary
and sufficient conditions for shaping the ratio vector of sub-channel gains of
two broadcast-channel receivers. We then apply this to two scenarios: First, in
digital multicasting we present a practical capacity-achieving scheme which
only uses scalar codes and linear processing. Then, we consider the joint
source-channel problem of transmitting a Gaussian source over a two-user MIMO
channel, where we show the existence of non-trivial cases, where the optimal
distortion pair (which for high signal-to-noise ratios equals the optimal
point-to-point distortions of the individual users) may be achieved by
employing a hybrid digital-analog scheme over the induced equivalent channel.
These scenarios demonstrate the advantage of choosing a modulation basis based
upon multiple links in the network, thus we coin the approach "network
modulation".Comment: Submitted to IEEE Tran. Signal Processing. Revised versio
Sufficient Dimension Reduction and Modeling Responses Conditioned on Covariates: An Integrated Approach via Convex Optimization
Given observations of a collection of covariates and responses , sufficient dimension reduction (SDR)
techniques aim to identify a mapping
with such that is independent of . The image
summarizes the relevant information in a potentially large number of covariates
that influence the responses . In many contemporary settings, the number
of responses is also quite large, in addition to a large number of
covariates. This leads to the challenge of fitting a succinctly parameterized
statistical model to , which is a problem that is usually not addressed
in a traditional SDR framework. In this paper, we present a computationally
tractable convex relaxation based estimator for simultaneously (a) identifying
a linear dimension reduction of the covariates that is sufficient with
respect to the responses, and (b) fitting several types of structured
low-dimensional models -- factor models, graphical models, latent-variable
graphical models -- to the conditional distribution of . We analyze the
consistency properties of our estimator in a high-dimensional scaling regime.
We also illustrate the performance of our approach on a newsgroup dataset and
on a dataset consisting of financial asset prices.Comment: 34 pages, 1 figur
Throughput Analysis and Optimization of Wireless-Powered Multiple Antenna Full-Duplex Relay Systems
We consider a full-duplex (FD) decode-and-forward system in which the
time-switching protocol is employed by the multi-antenna relay to receive
energy from the source and transmit information to the destination. The
instantaneous throughput is maximized by optimizing receive and transmit
beamformers at the relay and the time-split parameter. We study both optimum
and suboptimum schemes. The reformulated problem in the optimum scheme achieves
closed-form solutions in terms of transmit beamformer for some scenarios. In
other scenarios, the optimization problem is formulated as a semi-definite
relaxation problem and a rank-one optimum solution is always guaranteed. In the
suboptimum schemes, the beamformers are obtained using maximum ratio combining,
zero-forcing, and maximum ratio transmission. When beamformers have closed-form
solutions, the achievable instantaneous and delay-constrained throughput are
analytically characterized. Our results reveal that, beamforming increases both
the energy harvesting and loop interference suppression capabilities at the FD
relay. Moreover, simulation results demonstrate that the choice of the linear
processing scheme as well as the time-split plays a critical role in
determining the FD gains.Comment: Accepted for publication in IEEE Transactions on Communication
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
Beamforming Optimization for Full-Duplex Wireless-powered MIMO Systems
We propose techniques for optimizing transmit beamforming in a full-duplex
multiple-input-multiple-output (MIMO) wireless-powered communication system,
which consists of two phases. In the first phase, the wireless-powered mobile
station (MS) harvests energy using signals from the base station (BS), whereas
in the second phase, both MS and BS communicate to each other in a full-duplex
mode. When complete instantaneous channel state information (CSI) is available,
the BS beamformer and the time-splitting (TS) parameter of energy harvesting
are jointly optimized in order to obtain the BS-MS rate region. The joint
optimization problem is non-convex, however, a computationally efficient
optimum technique, based upon semidefinite relaxation and line-search, is
proposed to solve the problem. A sub-optimum zero-forcing approach is also
proposed, in which a closed-form solution of TS parameter is obtained. When
only second-order statistics of transmit CSI is available, we propose to
maximize the ergodic information rate at the MS, while maintaining the outage
probability at the BS below a certain threshold. An upper bound for the outage
probability is also derived and an approximate convex optimization framework is
proposed for efficiently solving the underlying non-convex problem. Simulations
demonstrate the advantages of the proposed methods over the sub-optimum and
half-duplex ones.Comment: 14 pages, accepte
Joint Secure Beamforming for Cognitive Radio Networks with Untrusted Secondary Users
In this paper, we consider simultaneous wireless information and power
transfer (SWIPT) in orthogonal frequency division multiple access (OFDMA)
systems with the coexistence of information receivers (IRs) and energy
receivers (ERs). The IRs are served with best-effort secrecy data and the ERs
harvest energy with minimum required harvested power. To enhance physical-layer
security and yet satisfy energy harvesting requirements, we introduce a new
frequency-domain artificial noise based approach. We study the optimal resource
allocation for the weighted sum secrecy rate maximization via transmit power
and subcarrier allocation. The considered problem is non-convex, while we
propose an efficient algorithm for solving it based on Lagrange duality method.
Simulation results illustrate the effectiveness of the proposed algorithm as
compared against other heuristic schemes.Comment: To appear in Globecom 201
- …