2,869 research outputs found
Downlink and Uplink Intelligent Reflecting Surface Aided Networks: NOMA and OMA
Intelligent reflecting surfaces (IRSs) are envisioned to provide
reconfigurable wireless environments for future communication networks. In this
paper, both downlink and uplink IRS-aided non-orthogonal multiple access (NOMA)
and orthogonal multiple access (OMA) networks are studied, in which an IRS is
deployed to enhance the coverage by assisting a cell-edge user device (UD) to
communicate with the base station (BS). To characterize system performance, new
channel statistics of the BS-IRS-UD link with Nakagami- fading are
investigated. For each scenario, the closed-form expressions for the outage
probability and ergodic rate are derived. To gain further insight, the
diversity order and high signal-to-noise ratio (SNR) slope for each scenario
are obtained according to asymptotic approximations in the high-SNR regime. It
is demonstrated that the diversity order is affected by the number of IRS
reflecting elements and Nakagami fading parameters, but the high-SNR slope is
not related to these parameters. Simulation results validate our analysis and
reveal the superiority of the IRS over the full-duplex decode-and-forward
relay.Comment: Accepted for publication in the IEEE Transactions on Wireless
Communication
Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces
Intelligent reflecting surfaces (IRSs) constitute a disruptive wireless communication technique capable of creating a controllable propagation environment. In this paper, we propose to invoke an IRS at the cell boundary of multiple cells to assist the downlink transmission to cell-edge users, whilst mitigating the inter-cell interference, which is a crucial issue in multicell communication systems. We aim for maximizing the weighted sum rate (WSR) of all users through jointly optimizing the active precoding matrices at the base stations (BSs) and the phase shifts at the IRS subject to each BS’s power constraint and unit modulus constraint. Both the BSs and the users are equipped with multiple antennas, which enhances the spectral efficiency by exploiting the spatial multiplexing gain. Due to the nonconvexity of the problem, we first reformulate it into an equivalent one, which is solved by using the block coordinate descent (BCD) algorithm, where the precoding matrices and phase shifts are alternately optimized. The optimal precoding matrices can be obtained in closed form, when fixing the phase shifts. A pair of efficient algorithms are proposed for solving the phase shift optimization problem, namely the Majorization-Minimization (MM) Algorithm and the Complex Circle Manifold (CCM) Method. Both algorithms are guaranteed to converge to at least locally optimal solutions. We also extend the proposed algorithms to the more general multiple-IRS and network MIMO scenarios. Finally, our simulation results confirm the advantages of introducing IRSs in enhancing the cell-edge user performance
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
Spectral and Energy Efficiency of IRS-Assisted MISO Communication with Hardware Impairments
In this letter, we analyze the spectral and energy efficiency of an intelligent reflecting surface (IRS)-assisted multiple-input single-output (MISO) downlink system with hardware impairments. An extended error vector magnitude (EEVM) model is utilized to characterize the impact of radio-frequency (RF) impairments at the access point (AP) and phase noise is considered at the IRS. We show that the spectral efficiency is limited due to the hardware impairments even when the numbers of AP antennas and IRS elements grow infinitely large, which is in contrast with the conventional case with ideal hardware. Moreover, the performance degradation at high SNR is shown to be mainly affected by the AP hardware impairments rather than by the phase noise at the IRS. We further obtain in closed form the optimal transmit power for energy efficiency maximization. Simulation results are provided to verify the obtained results
Overview of RIS-Enabled Secure Transmission in 6G Wireless Networks
As sixth-generation (6G) wireless communication networks evolve, privacy
concerns are expected due to the transmission of vast amounts of
security-sensitive private information. In this context, a reconfigurable
intelligent surface (RIS) emerges as a promising technology capable of
enhancing transmission efficiency and strengthening information security. This
study demonstrates how RISs can play a crucial role in making 6G networks more
secure against eavesdropping attacks. We discuss the fundamentals, and
standardization aspects of RISs, along with an in-depth analysis of
physical-layer security (PLS). Our discussion centers on PLS design using RIS,
highlighting aspects like beamforming, resource allocation, artificial noise,
and cooperative communications. We also identify the research issues, propose
potential solutions, and explore future perspectives. Finally, numerical
results are provided to support our discussions and demonstrate the enhanced
security enabled by RIS.Comment: Accepted for Digital Communications and Networks(DCN
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