53 research outputs found
Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces
In this paper, intelligent reflecting surfaces (IRSs) are employed to enhance
the physical layer security in a challenging radio environment. In particular,
a multi-antenna access point (AP) has to serve multiple single-antenna
legitimate users, which do not have line-of-sight communication links, in the
presence of multiple multi-antenna potential eavesdroppers whose channel state
information (CSI) is not perfectly known. Artificial noise (AN) is transmitted
from the AP to deliberately impair the eavesdropping channels for security
provisioning. We investigate the joint design of the beamformers and AN
covariance matrix at the AP and the phase shifters at the IRSs for maximization
of the system sum-rate while limiting the maximum information leakage to the
potential eavesdroppers. To this end, we formulate a robust nonconvex
optimization problem taking into account the impact of the imperfect CSI of the
eavesdropping channels. To address the non-convexity of the optimization
problem, an efficient algorithm is developed by capitalizing on alternating
optimization, a penalty-based approach, successive convex approximation, and
semidefinite relaxation. Simulation results show that IRSs can significantly
improve the system secrecy performance compared to conventional architectures
without IRS. Furthermore, our results unveil that, for physical layer security,
uniformly distributing the reflecting elements among multiple IRSs is
preferable over deploying them at a single IRS.Comment: 16 pages, 9 figures, submitted to IEEE Journal on Selected Areas in
Communications (JSAC), Special Issue on Wireless Networks Empowered by
Reconfigurable Intelligent Surface
Sum-Rate Maximization for Multiuser MISO Downlink Systems with Self-sustainable IRS
This paper investigates multiuser multi-input single-output (MISO) downlink
communications assisted by a self-sustainable intelligent reflection surface
(IRS), which can harvest power from the received signals. We study the joint
design of the beamformer at an access point (AP) and the phase shifts and the
power harvesting schedule at an IRS for maximizing the system sum-rate. The
design is formulated as a non-convex optimization problem taking into account
the capability of IRS elements to harvest wireless power for realizing
self-sustainability. Subsequently, we propose a computationally-efficient
alternating algorithm to obtain a suboptimal solution to the design problem.
Our simulation results unveil that: 1) there is a non-trivial trade-off between
the system sum-rate and self-sustainability in IRS-assisted systems; 2) the
performance gain achieved by the proposed scheme is improved with an increasing
number of IRS elements; 3) an IRS equipped with small bit-resolution discrete
phase shifters is sufficient to achieve a considerable system sum-rate of an
ideal case with continuous phase shifts.Comment: submitted to IEEE Global Commun. Conf. (GLOBECOM), Taiwan, Dec. 202
Chernoff Bounds and Saddlepoint Approximations for the Outage Probability in Intelligent Reflecting Surface Assisted Communication Systems
We analyze the outage probability of an intelligent reflecting surface
(IRS)-assisted communication network. A tight upper bound on the outage
probability is formulated based on the Chernoff inequality. Furthermore,
through an exact asymptotic (a large number of reflecting elements) analysis
based on a saddlepoint approximation, we derive closed-form expressions of the
outage probability for systems with and without a direct link and obtain the
corresponding diversity orders. Simulation results corroborate our theoretical
analysis and show the inaccuracies inherent in using the central limit theorem
(CLT) to analyze system performance. Our analysis is accurate even for a small
number of IRS elements in the high signal-to-noise ratio (SNR) regime.Comment: 5 pages, 2 figure
Secrecy Rate Maximization in Multi-IRS Millimeter Wave Networks
In this paper, the problem of physical layer security enhancement in a
millimeter-wave (mmWave) network equipped with multiple Intelligent Reflecting
Surfaces (IRSs) is investigated. In this network, the IRSs assist in signal
transmission from the Base Station (BS) to desired users and at the same time
in securing signals from an unauthorized eavesdropper. Our objective is to
maximize the secrecy rate by jointly optimizing the active and passive
beamformers at the base station and IRSs, respectively. The optimization
problem is non-convex and hence, we solve it by decomposing it into two
disjoint active and passive beamforming design sub-problems and then
iteratively solving them by alternating and Semi-Definite Relaxation (SDR)
techniques. Simulation results show the advantage of using multiple IRSs in
secrecy rate enhancement of the mmWave networks. In additio12n, we show how the
secrecy rate improves with the number of IRSs in the network and also with the
number of reflecting elements at the IRS.Comment: 12 pages, 5 figure
Robust and Secure Communications in Intelligent Reflecting Surface Assisted NOMA networks
This letter investigates secure transmission in an intelligent reflecting
surface (IRS) assisted non-orthogonal multiple access (NOMA) network. Consider
a practical eavesdropping scenario with imperfect channel state information of
the eavesdropper, we propose a robust beamforming scheme using artificial noise
to guarantee secure NOMA transmission with the IRS. A joint transmit
beamforming and IRS phase shift optimization problem is formulated to minimize
the transmit power. Since the problem is non-convex and challenging to resolve,
we develop an effective alternative optimization (AO) algorithm to obtain
stationary point solutions. Simulation results validate the security advantage
of the robust beamforming scheme and the effectiveness of the AO algorithm
Power-Efficient Resource Allocation for Multiuser MISO Systems via Intelligent Reflecting Surfaces
Intelligent reflecting surfaces (IRSs) are regarded as key enablers of
next-generation wireless communications, due to their capability of customizing
the wireless propagation environment. In this paper, we investigate
power-efficient resource allocation for IRS-assisted multiuser multiple-input
single-output (MISO) systems. To minimize the transmit power, both the
beamforming vectors at the access point (AP) and phase shifts at the IRS are
jointly optimized while taking into account the minimum required
quality-of-service (QoS) of the users. To tackle the non-convexity of the
formulated optimization problem, an inner approximation (IA) algorithm is
developed. Unlike existing designs, which cannot guarantee local optimality,
the proposed algorithm is guaranteed to converge to a Karush-Kuhn-Tucker (KKT)
solution. Our simulation results show the effectiveness of the proposed
algorithm compared to baseline schemes and reveal that deploying IRSs is more
promising than leveraging multiple antennas at the AP in terms of energy
efficiency.Comment: 6 pages, 4 figures, submitted to IEEE Global Commun. Conf.
(GLOBECOM), Taiwan, Dec. 202
Study of Intelligent Reflective Surface Assisted Communications with One-bit Phase Adjustments
We analyse the performance of a communication link assisted by an intelligent
reflective surface (IRS) positioned in the far field of both the source and the
destination. A direct link between the transmitting and receiving devices is
assumed to exist. Perfect and imperfect phase adjustments at the IRS are
considered. For the perfect phase configuration, we derive an approximate
expression for the outage probability in closed form. For the imperfect phase
configuration, we assume that each element of the IRS has a one-bit phase
shifter (0{\deg}, 180{\deg}) and an expression for the outage probability is
obtained in the form of an integral. Our formulation admits an exact asymptotic
(high SNR) analysis, from which we obtain the diversity orders for systems with
and without phase errors. We show these are N + 1 and (N + 3)/2, respectively.
Numerical results confirm the theoretical analysis and verify that the reported
results are more accurate than methods based on the central limit theorem
(CLT).Comment: 6 pages, 3 figures. Accepted in 2020 IEEE GLOBECO
Wireless Communication via Double IRS: Channel Estimation and Passive Beamforming Designs
In this letter, we study efficient channel estimation and passive beamforming
designs for a double-intelligent reflecting surface (IRS) aided single-user
communication system, where a user communicates with an access point (AP) via
the cascaded user-IRS 1-IRS 2-AP double-reflection link. First, a general
channel estimation scheme is proposed for the system under any arbitrary
inter-IRS channel, where all coefficients of the cascaded channel are
estimated. Next, for the typical scenario with a line-of-sight (LoS)-dominant
inter-IRS channel, we propose another customized scheme to estimate two
signature vectors of the rank-one cascaded channel with significantly less
channel training time than the first scheme. For the two proposed channel
estimation schemes, we further optimize their corresponding cooperative passive
beamforming for data transmission to maximize the achievable rate with the
training overhead and channel estimation error taken into account. Numerical
results show that deploying two cooperative IRSs with the proposed channel
estimation and passive beamforming designs achieves significant rate
enhancement as compared to the conventional case of single IRS deployment.Comment: Submitted to IEEE for possible publication. This paper considers a
new double-IRS aided communication system and studies its channel estimation
and passive beamforming design
Intelligent Reflecting Surface Aided Multicasting with Random Passive Beamforming
In this letter, we consider a multicast system where a single-antenna
transmitter sends a common message to multiple single-antenna users, aided by
an intelligent reflecting surface (IRS) equipped with passive reflecting
elements. Prior works on IRS have mostly assumed the availability of channel
state information (CSI) for designing its passive beamforming. However, the
acquisition of CSI requires substantial training overhead that increases with
. In contrast, we propose in this letter a novel \emph{random passive
beamforming} scheme, where the IRS performs independent random reflection for
times in each channel coherence interval without the need of CSI
acquisition. For the proposed scheme, we first derive a closed-form
approximation of the outage probability, based on which the optimal with
best outage performance can be efficiently obtained. Then, for the purpose of
comparison, we derive a lower bound of the outage probability with traditional
CSI-based passive beamforming. Numerical results show that a small is
preferred in the high-outage regime (or with high rate target) and the optimal
becomes larger as the outage probability decreases (or as the rate target
decreases). Moreover, the proposed scheme significantly outperforms the
CSI-based passive beamforming scheme with training overhead taken into
consideration when and/or the number of users are large, thus offering a
promising CSI-free alternative to existing CSI-based schemes.Comment: To appear in IEEE Wireless Communications Lette
Resource Allocation for Intelligent Reflecting Surface-Assisted Cognitive Radio Networks
In this paper, we investigate resource allocation algorithm design for
intelligent reflecting surface (IRS)-assisted multiuser cognitive radio (CR)
systems. In particular, an IRS is deployed to mitigate the interference caused
by the secondary network to the primary users. The beamforming vectors at the
base station (BS) and the phase shift matrix at the IRS are jointly optimized
for maximization of the sum rate of the secondary system. The algorithm design
is formulated as a non-convex optimization problem taking into account the
maximum interference tolerance of the primary users. To tackle the resulting
non-convex optimization problem, we propose an alternating optimization-based
suboptimal algorithm exploiting semidefinite relaxation, the penalty method,
and successive convex approximation. Our simulation results show that the
system sum rate is dramatically improved by our proposed scheme compared to two
baseline schemes. Moreover, our results also illustrate the benefits of
deploying IRSs in CR networks.Comment: 5 pages, 3 figures, submitted to conferenc
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