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1. Joint Downlink and Uplink Optimization for RIS-Aided FDD MIMO Communication Systems

   https://doi.org/10.1109/TWC.2024.3358291  

   Lee, Gyoseung; Lee, Hyeongtaek; Kim, Donghwan; Chung, Jaehoon; Swindlehurst, A Lee; Choi, Junil (August 2024, IEEE Transactions on Wireless Communications)

   This paper investigates reconfigurable intelligent surface (RIS)-aided frequency division duplexing (FDD) communication systems. Since the downlink and uplink signals are simultaneously transmitted in FDD, the phase shifts at the RIS should be designed to support both transmissions. Considering a single-user multiple-input multiple-output system, we formulate a weighted sum-rate maximization problem to jointly maximize the downlink and uplink system performance. To tackle the non-convex optimization problem, we adopt an alternating optimization (AO) algorithm, in which two phase shift optimization techniques are developed to handle the unit-modulus constraints induced by the reflection coefficients at the RIS. The first technique exploits the manifold optimization-based algorithm, while the second uses a lower-complexity AO approach. Numerical results verify that the proposed techniques rapidly converge to local optima and significantly improve the overall system performance compared to existing benchmark schemes. 

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2. Intelligent Reflecting Surface Empowered Self-Interference Cancellation in Full-Duplex Systems

   https://doi.org/10.1109/TCOMM.2023.3347576  

   Qiu, Chi; Wu, Qingqing; Hua, Meng; Chen, Wen; Ma, Shaodan; Hou, Fen; Ng, Derrick_Wing Kwan; Swindlehurst, A Lee (May 2024, IEEE Transactions on Communications)

   Compared with traditional half-duplex wireless systems, the application of emerging full-duplex (FD) technology can potentially double the system capacity theoretically. However, conventional techniques for suppressing self-interference (SI) adopted in FD systems require exceedingly high power consumption and expensive hardware. In this paper, we consider employing an intelligent reflecting surface (IRS) in the proximity of an FD base station (BS) to mitigate SI for simultaneously receiving data from uplink users and transmitting information to downlink users. The objective considered is to maximize the system weighted sum-rate by jointly optimizing the IRS phase shifts, the BS transmit beamformers, and the transmit power of the uplink users. To visualize the role of the IRS in SI cancellation, we first study a simple scenario with one downlink user and one uplink user. To address the formulated non-convex problem, a low-complexity algorithm based on successive convex approximation is proposed. For the more general case considering multiple downlink and uplink users, an efficient alternating optimization algorithm based on element-wise optimization is proposed. Numerical results demonstrate that the FD system with the proposed schemes can achieve a larger gain over the half-duplex system, and the IRS is able to achieve a balance between suppressing SI and providing beamforming gain. 

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3. Machine Learning-based Reconfigurable Intelligent Surface-aided MIMO Systems

   https://doi.org/10.1109/SPAWC51858.2021.9593256  

   Nguyen, Nhan Thanh; Nguyen, Ly V.; Huynh-The, Thien; Nguyen, Duy H.; Lee Swindlehurst, A.; Juntti, Markku (September 2021, Proc. IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC))

   Reconfigurable intelligent surface (RIS) technology has recently emerged as a spectral- and cost-efficient approach for wireless communications systems. However, existing hand-engineered schemes for passive beamforming design and optimization of RIS, such as the alternating optimization (AO) approaches, require a high computational complexity, especially for multiple-input-multiple-output (MIMO) systems. To over-come this challenge, we propose a low-complexity unsupervised learning scheme, referred to as learning-phase-shift neural net-work (LPSNet), to efficiently find the solution to the spectral efficiency maximization problem in RIS-aided MIMO systems. In particular, the proposed LPSNet has an optimized input structure and requires a small number of layers and nodes to produce efficient phase shifts for the RIS. Simulation results for a 16 × 2 MIMO system assisted by an RIS with 40 elements show that the LPSNet achieves 97.25% of the SE provided by the AO counterpart with more than a 95% reduction in complexity. 

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4. RIS-Aided Interference Cancellation for Joint Device-to-Device and Cellular Communications

   https://doi.org/10.1109/ICCWorkshops59551.2024.10615548  

   Nguyen, Ly V; Swindlehurst, A Lee (June 2024, IEEE)

   Joint device-to-device (D2D) and cellular communication is a promising technology for enhancing the spectral efficiency of future wireless networks. However, the interference management problem is challenging since the operating devices and the cellular users share the same spectrum. The emerging reconfigurable intelligent surfaces (RIS) technology is a potentially ideal solution for this interference problem since RISs can shape the wireless channel in desired ways. This paper considers an RIS-aided joint D2D and cellular communication system where the RIS is exploited to cancel interference to the D2D links and maximize the minimum signal-to-interference plus noise (SINR) of the device pairs and cellular users. First, we adopt a popular alternating optimization (AO) approach to solve the minimum SINR maximization problem. Then, we propose an interference cancellation (IC)-based approach whose complexity is much lower than that of the AO algorithm. We derive a representation for the RIS phase shift vector which cancels the interference to the D2D links. Based on this representation, the RIS phase shift optimization problem is transformed into an effective D2D channel optimization. We show that the AO approach can converge faster and can even give better performance when it is initialized by the proposed IC solution. We also show that for the case of a single D2D pair, the proposed IC approach can be implemented with limited feedback from the single receive device. 

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5. RIS-Assisted Interference Mitigation for Uplink NOMA

   https://doi.org/10.1109/WCNC55385.2023.10119107  

   Tabeshnezhad, Azadeh; Swindlehurst, A. Lee; Svensson, Tommy (March 2023, 2023 IEEE Wireless Communications and Networking Conference (WCNC))

   Non-orthogonal multiple access (NOMA) has become a promising technology for next-generation wireless communications systems due to its capability to provide access for multiple users on the same resource. In this paper, we consider an uplink power-domain NOMA system aided by a reconfigurable intelligent surface (RIS) in the presence of a jammer that aims to maximize its interference on the base station (BS) uplink receiver. We consider two kinds of RISs, a regular RIS whose elements can only change the phase of the incoming wave, and an RIS whose elements can also attenuate the incoming wave. Our aim is to minimize the total power transmitted by the user terminals under quality-of-service constraints by controlling both the propagation from the users and the jammer to the BS with help of the RIS. The resulting objective function and constraints are both non-linear and non-convex, so we address this problem using numerical optimization. Our numerical results show that the RIS can help to dramatically reduce the per user required transmit power in an interference-limited scenario. 

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