177 research outputs found
Robust Design for Intelligent Reflecting Surface-Assisted Secrecy SWIPT Network
This paper investigates the robust beamforming design in a secrecy multiple-input single-output (MISO) network aided by the intelligent reflecting surface (IRS) with simultaneous wireless information and power transfer (SWIPT). Specifically, by considering that the energy receivers (ERs) are potential eavesdroppers (Eves) and imperfect channel state information (CSI) of the direct and cascaded channels can be obtained, we investigate the max-min fairness robust secrecy design. The objective is to maximize the minimum robust information rate among the legitimate information receivers (IRs). To solve the formulated non-convex design problem in bounded and probabilistic CSI error models, we utilize the alternating optimization (AO) and successive convex approximation (SCA) methods to obtain an approximate problem. Then, an iteration-based algorithm framework was proposed, where the unit modulus constraint (UMC) of the IRS is handled by the penalty dual decomposition (PDD) method. Moreover, a stochastic SCA method is proposed to handle the outage constrained design with statistical CSI. Finally, simulation results validate the promising performance of the proposed design
Exploiting Amplitude Control in Intelligent Reflecting Surface Aided Wireless Communication with Imperfect CSI
Intelligent reflecting surface (IRS) is a promising new paradigm to achieve
high spectral and energy efficiency for future wireless networks by
reconfiguring the wireless signal propagation via passive reflection. To reap
the potential gains of IRS, channel state information (CSI) is essential,
whereas channel estimation errors are inevitable in practice due to limited
channel training resources. In this paper, in order to optimize the performance
of IRS-aided multiuser systems with imperfect CSI, we propose to jointly design
the active transmit precoding at the access point (AP) and passive reflection
coefficients of IRS, each consisting of not only the conventional phase shift
and also the newly exploited amplitude variation. First, the achievable rate of
each user is derived assuming a practical IRS channel estimation method, which
shows that the interference due to CSI errors is intricately related to the AP
transmit precoders, the channel training power and the IRS reflection
coefficients during both channel training and data transmission. Then, for the
single-user case, by combining the benefits of the penalty method, Dinkelbach
method and block successive upper-bound minimization (BSUM) method, a new
penalized Dinkelbach-BSUM algorithm is proposed to optimize the IRS reflection
coefficients for maximizing the achievable data transmission rate subjected to
CSI errors; while for the multiuser case, a new penalty dual decomposition
(PDD)-based algorithm is proposed to maximize the users' weighted sum-rate.
Simulation results are presented to validate the effectiveness of our proposed
algorithms as compared to benchmark schemes. In particular, useful insights are
drawn to characterize the effect of IRS reflection amplitude control
(with/without the conventional phase shift) on the system performance under
imperfect CSI.Comment: 15 pages, 10 figures, accepted by IEEE Transactions on Communication
RIS-Aided MIMO Systems with Hardware Impairments: Robust Beamforming Design and Analysis
Reconfigurable intelligent surface (RIS) has been anticipated to be a novel
cost-effective technology to improve the performance of future wireless
systems. In this paper, we investigate a practical RIS-aided
multiple-input-multiple-output (MIMO) system in the presence of transceiver
hardware impairments, RIS phase noise and imperfect channel state information
(CSI). Joint design of the MIMO transceiver and RIS reflection matrix to
minimize the total average mean-square-error (MSE) of all data streams is
particularly considered. This joint design problem is non-convex and
challenging to solve due to the newly considered practical imperfections. To
tackle the issue, we first analyze the total average MSE by incorporating the
impacts of the above system imperfections. Then, in order to handle the tightly
coupled optimization variables and non-convex NP-hard constraints, an efficient
iterative algorithm based on alternating optimization (AO) framework is
proposed with guaranteed convergence, where each subproblem admits a
closed-form optimal solution by leveraging the majorization-minimization (MM)
technique. Moreover, via exploiting the special structure of the unit-modulus
constraints, we propose a modified Riemannian gradient ascent (RGA) algorithm
for the discrete RIS phase shift optimization. Furthermore, the optimality of
the proposed algorithm is validated under line-of-sight (LoS) channel
conditions, and the irreducible MSE floor effect induced by imperfections of
both hardware and CSI is also revealed in the high signal-to-noise ratio (SNR)
regime. Numerical results show the superior MSE performance of our proposed
algorithm over the adopted benchmark schemes, and demonstrate that increasing
the number of RIS elements is not always beneficial under the above system
imperfections.Comment: 30 pages, 8 figures. This paper has been submitted to IEEE journal
for possible publicatio
Robust Secure Transmission for Active RIS Enabled Symbiotic Radio Multicast Communications
In this paper, we propose a robust secure transmission scheme for an active
reconfigurable intelligent surface (RIS) enabled symbiotic radio (SR) system in
the presence of multiple eavesdroppers (Eves). In the considered system, the
active RIS is adopted to enable the secure transmission of primary signals from
the primary transmitter to multiple primary users in a multicasting manner, and
simultaneously achieve its own information delivery to the secondary user by
riding over the primary signals. Taking into account the imperfect channel
state information (CSI) related with Eves, we formulate the system power
consumption minimization problem by optimizing the transmit beamforming and
reflection beamforming for the bounded and statistical CSI error models, taking
the worst-case SNR constraints and the SNR outage probability constraints at
the Eves into considerations, respectively. Specifically, the S-Procedure and
the Bernstein-Type Inequality are implemented to approximately transform the
worst-case SNR and the SNR outage probability constraints into tractable forms,
respectively. After that, the formulated problems can be solved by the proposed
alternating optimization (AO) algorithm with the semi-definite relaxation and
sequential rank-one constraint relaxation techniques. Numerical results show
that the proposed active RIS scheme can reduce up to 27.0% system power
consumption compared to the passive RIS.Comment: 32 Pages, 12 figures, accepted to IEEE Transactions on Wireless
Communication
A Framework of Robust Transmission Design for IRS-Aided MISO Communications With Imperfect Cascaded Channels
Intelligent reflection surface (IRS) has recently been recognized as a
promising technique to enhance the performance of wireless systems due to its
ability of reconfiguring the signal propagation environment. However, the
perfect channel state information (CSI) is challenging to obtain at the base
station (BS) due to the lack of radio frequency (RF) chains at the IRS. Since
most of the existing channel estimation methods were developed to acquire the
cascaded BS-IRS-user channels, this paper is the first work to study the robust
beamforming based on the imperfect cascaded BS-IRS-user channels at the
transmitter (CBIUT). Specifically, the transmit power minimization problems are
formulated subject to the worst-case rate constraints under the bounded CSI
error model and the rate outage probability constraints under the statistical
CSI error model, respectively. After approximating the worst-case rate
constraints by using the S-procedure and the rate outage probability
constraints by using the Bernstein-type inequality, the reformulated problems
can be efficiently solved. Numerical results show that the negative impact of
the CBIUT error on the system performance is greater than that of the direct
CSI error.Comment: Accepted in IEEE Transactions on Signal Processing. Keywords:
Intelligent reflecting surface (IRS), reconfigurable intelligent surface
(RIS), robust transmission desig
Robust Hybrid Beamforming Design for Multi-RIS Assisted MIMO System with Imperfect CSI
Reconfigurable intelligent surface (RIS) has been developed as a promising approach to enhance the performance of fifth-generation (5G) systems through intelligently reconfiguring the reflection elements. However, RIS-assisted beamforming design highly depends on the channel state information (CSI) and RIS’s location, which could have a significant impact on system performance. In this paper, the robust beamforming design is investigated for a RIS-assisted multiuser millimeter wave system with imperfect CSI, where the weighted sum-rate maximization problem (WSM) is formulated to jointly optimize transmit beamforming of the BS, RIS placement and reflect beamforming of the RIS. The considered WSM maximization problem includes CSI error, phase shifts matrices, transmit beamforming as well as RIS placement variables, which results in a complicated nonconvex problem. To handle this problem, the original problem is divided into a series of subproblems, where the location of RIS, transmit/reflect beamforming and CSI error are optimized iteratively. Then, a multiobjective evolutionary algorithm is introduced to gradient projection-based alternating optimization, which can alleviate the performance loss caused by the effect of imperfect CSI. Simulation results reveal that the proposed scheme can potentially enhance the performance of existing wireless communication, especially considering a desirable trade-off among beamforming gain, user priority and error factor
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