Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization

By Yifei Yang, Beixiong Zheng, Shuowen Zhang, Rui Zhang. IEEE Transactions on Communications, 2019

736 citations recorded by the source corpus.

Intelligent reflecting surface (IRS) is a promising new technology for achieving both spectrum and energy efficient wireless communication systems in the future. However, existing works on IRS mainly consider frequency-flat channels and assume perfect knowledge of channel state information (CSI) at the transmitter. Motivated by the above, in this paper we study an IRS-enhanced orthogonal frequency division multiplexing (OFDM) system under frequency-selective channels and propose a practical transmission protocol with channel estimation. First, to reduce the overhead in channel training as well as exploit the channel spatial correlation, we propose a novel IRS elements grouping method, where each group consists of a set of adjacent IRS elements that share a common reflection coefficient. Based on this method, we propose a practical transmission protocol where only the combined channel of each group needs to be estimated, thus substantially reducing the training overhead. Next, with any given grouping and estimated CSI, we formulate the problem to maximize the achievable rate by jointly optimizing the transmit power allocation and the IRS passive array reflection coefficients. Although the formulated problem is non-convex and thus difficult to solve, we propose an efficient algorithm to obtain a high-quality suboptimal solution for it, by alternately optimizing the power allocation and the passive array coefficients in an iterative manner, along with a customized method for the initialization. Simulation results show that the proposed design significantly improves the OFDM link rate performance as compared to the case without using IRS. Moreover, it is shown that there exists an optimal size for IRS elements grouping which achieves the maximum achievable rate due to the practical trade-off between the training overhead and IRS passive beamforming flexibility.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/463805d049310293f4661a1970d1cd3375d6102b

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Citations in the corpus

Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints (2019, background): “The joint active and passive beamforming design was also investigated in other system setups, e.g., physical layer security [9]– [12], orthogonal frequency division multiplexing (OFDM) systems [18], [19], and non-orthogonal multiple access [13], [14].”
Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison (2019, background): “straints and the analysis of the achievable performance of RISs for application to frequency-selective fading channels is an open research issue [25].”
Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks (2019, methodology): “Then, in [38], this method is modified by grouping the adjacent elements to reduce the training overhead.”
Double-IRS Assisted Multi-User MIMO: Cooperative Passive Beamforming Design (2020, background): “, orthogonal frequency division multiplexing (OFDM) [6]– [10], multi-antenna communication [11]–[13], non-orthogonal multiple access (NOMA) [14]–[16], etc.”
An Overview of Signal Processing Techniques for RIS/IRS-Aided Wireless Systems (2021, neutral): “• On-off Scheme [43], [44]: The simplest scheme is the on-off scheme adopted in [43], [44].”
Multicell MIMO Communications Relying on Intelligent Reflecting Surfaces (2019, methodology): “The sum rate maximization problem of IRS-aided orthogonal frequency division multiplexing (OFDM) was carried out by jointly optimizing the power allocation and phase shifts [14] and the successive convex approximation (SCA) technique was invoked for finding the optimal phase shifts.”
Modeling and Architecture Design of Reconfigurable Intelligent Surfaces Using Scattering Parameter Network Analysis (2020, background): “Furthermore, RIS has also been investigated to provide performance enhancement in orthogonal frequency division multiplexing (OFDM) [12], [13], non-orthogonal multiple access (NOMA) [14], and emerging areas such as secure wireless communication [15], backscatter communication [16], simultaneous…”
Latency Minimization for Intelligent Reflecting Surface Aided Mobile Edge Computing (2019, methodology): “[29] grouped the IRS elements, where each group shares the same phase shift coefficient, and optimized the power allocation and phase shift in orthogonal frequency division multiplexing (OFDM)based wireless systems.”
An Optimal Channel Estimation Scheme for Intelligent Reflecting Surfaces Based on a Minimum Variance Unbiased Estimator (2019, methodology): “We consider a model with all IRS elements passive as in [3, 8, 9].”
Intelligent Reflecting Surface Aided MIMO Broadcasting for Simultaneous Wireless Information and Power Transfer (2019, background): “As a further advance, the authors of [9] considered realistic frequencyselective channels.”
Reconfigurable Intelligent Surfaces for Localization: Position and Orientation Error Bounds (2020, methodology): “A step forward will be the analysis of the localization performance limits in multi-RISs scenarios, or the design of ad-hoc localization algorithms in the presence of multi-scatterers, accounting for proper channel models [83].”
Reconfigurable Intelligent Surfaces: Principles and Opportunities (2020, methodology): “Developing low complexity channel estimation approaches [8], [89] and robust joint beamforming schemes [80], [82] constitute a”
Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead (2020, neutral): “In [153], the authors study an RIS-aided system model and propose a practical transmission protocol and channel estimation algorithm, by assuming an orthogonal frequency division multiplexing (OFDM) transmission scheme and a frequency-selective channel.”
Intelligent Reflecting Surface Enhanced Wireless Networks: Two-Timescale Beamforming Optimization (2019, methodology): “In [14], an IRS element-grouping method was also proposed to reduce the training overhead, at the cost of degraded passive beamforming performance of the IRS.”
Channel Estimation and Passive Beamforming for Intelligent Reflecting Surface: Discrete Phase Shift and Progressive Refinement (2019, methodology): “Moreover, IRS passive beamforming has been jointly designed with other communication techniques, such as orthogonal frequency division multiplexing (OFDM) [14], MIMO [15], [16], non-orthogonal multiple access (NOMA) [17]–[20], physical-layer security [21]–[24], simultaneous wireless information and ”
Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications (2020, background): “The N -element RIS should be ﬁrst partitioned in groups of non-overlapping sub-cells, such that each group’s number of elements meets the feasibility conditions (i.e., less or equal to M and K ) [52].”
Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts (2019, background): “In contrast, for the second approach without receive RF chains at the IRS, the IRS reflection patterns can be designed together with the uplink pilots to estimate the concatenated AP-IRS-user channels [18], [36].”