skip to main content
US FlagAn official website of the United States government
dot gov icon
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
https lock icon
Secure .gov websites use HTTPS
A lock ( lock ) or https:// means you've safely connected to the .gov website. Share sensitive information only on official, secure websites.


Title: Machine Learning-based Reconfigurable Intelligent Surface-aided MIMO Systems
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.  more » « less
Award ID(s):
2107182 2030029
PAR ID:
10341044
Author(s) / Creator(s):
; ; ; ; ;
Date Published:
Journal Name:
Proc. IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Page Range / eLocation ID:
101 to 105
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Due to the simultaneous downlink and uplink transmissions in reconfigurable intelligent surface (RIS)-empowered frequency division duplexing (FDD) communication systems, it is necessary to design the RIS phase shifts to balance the performance of both directions at the same time. Focusing on a single-user multiple-input multiple-output system, we aim to maximize a weighted sum-rate for the downlink and uplink. To address the resulting non-convex optimization problem, we employ an alternating optimization (AO) algorithm, which includes two techniques for optimizing the phase shifts at the RIS. A manifold optimization-based algorithm is applied for the first technique, and a lower-complexity AO approach is developed for the second. Our numerical results demonstrate that the proposed algorithms lead to substantial enhancement of the entire system compared to existing baseline schemes. 
    more » « less
  2. 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. 
    more » « less
  3. 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. 
    more » « less
  4. This paper explores the use of reconfigurable intelligent surfaces (RISs) for moving target detection in multi-input multi-output (MIMO) radar. Unlike previous related works that ignore the propa-gation delay difference between the direct path and the RIS-reflected path, we examine the detection problem in RIS-assisted MIMO radar by taking into account the effect of asynchronous propagation. Specifically, we first develop a general signal model for RIS-aided MIMO radar with multiple asynchronous RISs and arbitrary wave-forms. Next, we formulate the RIS design problem by maximizing the overall received signal energy. The resulting optimization problem is non-convex, which is solved with semidefinite relaxation (SDR) techniques. A coherent detector is introduced for target detection. Finally, numerical results are presented to demonstrate the performance of the RIS-aided MIMO radar in comparison with the conventional MIMO radar. 
    more » « less
  5. Millimeter-wave (mmWave) communications is a key enabler towards realizing enhanced Mobile Broadband (eMBB) as a key promise of 5G and beyond, due to the abundance of bandwidth available at mmWave bands. An mmWave coverage map consists of blind spots due to shadowing and fading especially in dense urban environments. Beam-forming employing massive MIMO is primarily used to address high attenuation in the mmWave channel. Due to their ability in manipulating the impinging electromagnetic waves in an energy-efficient fashion, Reconfigurable Intelligent Surfaces (RISs) are considered a great match to complement the massive MIMO systems in realizing the beam-forming task and therefore effectively filling in the mmWave coverage gap. In this paper, we propose a novel RIS architecture, namely RIS-UPA where the RIS elements are arranged in a Uniform Planar Array (UPA). We show how RIS-UPA can be used in an RIS-aided MIMO system to fill the coverage gap in mmWave by forming beams of a custom footprint, with optimized main lobe gain, minimum leakage, and fairly sharp edges. Further, we propose a configuration for RIS-UPA that can support multiple two-way communication pairs, simultaneously. We theoretically obtain closed-form low-complexity solutions for our design and validate our theoretical findings by extensive numerical experiments. 
    more » « less