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Register a new userTwo-Way Passive Beamforming Design for RIS-Aided FDD Communication Systems
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Added by
Bei Guo
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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Reconfigurable intelligent surfaces (RISs) are able to provide passive beamforming gain via low-cost reflecting elements and hence improve wireless link quality. This work considers two-way passive beamforming design in RIS-aided frequency division duplexing (FDD) systems where the RIS reflection coefficients are the same for downlink and uplink and should be optimized for both directions simultaneously. We formulate a joint optimization of the transmit/receive beamformers at the base station (BS) and the RIS reflection coefficients. The objective is to maximize the weighted sum of the downlink and uplink rates, where the weighting parameter is adjustable to obtain different achievable downlink-uplink rate pairs. We develop an efficient manifold optimization algorithm to obtain a stationary solution. For comparison, we also introduce two heuristic designs based on one-way optimization, namely, time-sharing and phase-averaging. Simulation results show that the proposed manifold-based two-way optimization design significantly enlarges the achievable downlink-uplink rate region compared with the two heuristic designs. It is also shown that phase-averaging is superior to time-sharing when the number of RIS elements is large.
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This paper considers a reconfigurable intelligent surface (RIS)-aided millimeter wave (mmWave) downlink communication system where hybrid analog-digital beamforming is employed at the base station (BS). We formulate a power minimization problem by jointly optimizing hybrid beamforming at the BS and the response matrix at the RIS, under signal-to-interference-plus-noise ratio (SINR) constraints. The problem is highly challenging due to the non-convex SINR constraints as well as the non-convex unit-modulus constraints for both the phase shifts at the RIS and the analog beamforming at the BS. A penalty-based algorithm in conjunction with the manifold optimization technique is proposed to handle the problem, followed by an individual optimization method with much lower complexity. Simulation results show that the proposed algorithm outperforms the state-of-art algorithm. Results also show that the joint optimization of RIS response matrix and BS hybrid beamforming is much superior to individual optimization.
This paper investigates the passive beamforming and deployment design for an intelligent reflecting surface (IRS) aided full-duplex (FD) wireless system, where an FD access point (AP) communicates with an uplink (UL) user and a downlink (DL) user simultaneously over the same time-frequency dimension with the help of IRS. Under this setup, we consider three deployment cases: 1) two distributed IRSs placed near the UL user and DL user, respectively; 2) one centralized IRS placed near the DL user; 3) one centralized IRS placed near the UL user. In each case, we aim to minimize the weighted sum transmit power consumption of the AP and UL user by jointly optimizing their transmit power and the passive reflection coefficients at the IRS (or IRSs), subject to the UL and DL users rate constraints and the uni-modulus constraints on the IRS reflection coefficients. First, we analyze the minimum transmit power required in the IRS-aided FD system under each deployment scheme, and compare it with that of the corresponding half-duplex (HD) system. We show that the FD system outperforms its HD counterpart for all IRS deployment schemes, while the distributed deployment further outperforms the other two centralized deployment schemes. Next, we transform the challenging power minimization problem into an equivalent but more tractable form and propose an efficient algorithm to solve it based on the block coordinate descent (BCD) method. Finally, numerical results are presented to validate our analysis as well as the efficacy of the proposed passive beamforming design.
The concept of reconfigurable intelligent surface (RIS) has been proposed to change the propagation of electromagnetic waves, e.g., reflection, diffraction, and refraction. To accomplish this goal, the phase values of the discrete RIS units need to be optimized. In this paper, we consider RIS-aided millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems for both accurate positioning and high data-rate transmission. We propose an adaptive phase shifter design based on hierarchical codebooks and feedback from the mobile station (MS). The benefit of the scheme lies in that the RIS does not require deployment of any active sensors and baseband processing units. During the update process of phase shifters, the combining vector at the MS is also sequentially refined. Simulation results show the performance improvement of the proposed algorithm over the random design scheme, in terms of both positioning accuracy and data rate. Moreover, the performance converges to exhaustive search scheme even in the low signal-to-noise ratio regime.
Thanks to the line-of-sight (LoS) transmission and flexibility, unmanned aerial vehicles (UAVs) effectively improve the throughput of wireless networks. Nevertheless, the LoS links are prone to severe deterioration by complex propagation environments, especially in urban areas. Reconfigurable intelligent surfaces (RISs), as a promising technique, can significantly improve the propagation environment and enhance communication quality by intelligently reflecting the received signals. Motivated by this, the joint UAV trajectory and RISs passive beamforming design for a novel RIS-assisted UAV communication system is investigated to maximize the average achievable rate in this letter. To tackle the formulated non-convex problem, we divide it into two subproblems, namely, passive beamforming and trajectory optimization. We first derive a closed-form phase-shift solution for any given UAV trajectory to achieve the phase alignment of the received signals from different transmission paths. Then, with the optimal phase-shift solution, we obtain a suboptimal trajectory solution by using the successive convex approximation (SCA) method. Numerical results demonstrate that the proposed algorithm can considerably improve the average achievable rate of the system.
In this paper, we consider a reconfigurable intelligent surface (RIS)-assisted two-way relay network, in which two users exchange information through the base station (BS) with the help of an RIS. By jointly designing the phase shifts at the RIS and beamforming matrix at the BS, our objective is to maximize the minimum signal-to-noise ratio (SNR) of the two users, under the transmit power constraint at the BS. We first consider the single-antenna BS case, and propose two algorithms to design the RIS phase shifts and the BS power amplification parameter, namely the SNR-upper-bound-maximization (SUM) method, and genetic-SNR-maximization (GSM) method. When there are multiple antennas at the BS, the optimization problem can be approximately addressed by successively solving two decoupled subproblems, one to optimize the RIS phase shifts, the other to optimize the BS beamforming matrix. The first subproblem can be solved by using SUM or GSM method, while the second subproblem can be solved by using optimized beamforming or maximum-ratio-beamforming method. The proposed algorithms have been verified through numerical results with computational complexity analysis.
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