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Stacked Intelligent Metasurface-Enhanced MIMO OFDM Wideband Communication Systems

Zheao Li, Jiancheng An, Chau Yuen

TL;DR

This work introduces a fully-analog stacked intelligent metasurface (SIM) architecture for wideband MIMO-OFDM that performs beamforming in the electromagnetic wave domain to diagonalize the end-to-end channel and suppress inter-antenna interference. By cascading multiple metasurface layers (L TX-SIM and K RX-SIM), the system creates parallel subchannels and enables fully-analog spatial multiplexing with $N_{RF}=N_{TX}=S$, reducing baseband processing. The authors formulate a multi-carrier phase-shift optimization problem and solve it with a BCD-PCCP algorithm, achieving near-diagonal end-to-end channels across a finite effective bandwidth $B_e$ (around 20 MHz in their setup) and demonstrating substantial capacity gains (e.g., >$300\%$ over center-frequency configurations at 28 GHz with 16 subcarriers). Compared with fully-digital, hybrid, and DMA-based metasurface approaches, the SIM_MC configuration delivers significant capacity improvements with lower hardware complexity and energy consumption, highlighting its potential for high-capacity, energy-efficient wideband wireless links.

Abstract

Multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems rely on digital or hybrid digital and analog designs for beamforming against frequency-selective fading, which suffer from high hardware complexity and energy consumption. To address this, this work introduces a fully-analog stacked intelligent metasurfaces (SIM) architecture that directly performs wave-domain beamforming, enabling diagonalization of the end-to-end channel matrix and inherently eliminating inter-antenna interference (IAI) for MIMO OFDM transmission. By leveraging cascaded programmable metasurface layers, the proposed system establishes multiple parallel subchannels, significantly improving multi-carrier transmission efficiency while reducing hardware complexity. To optimize the SIM phase shift matrices, a block coordinate descent and penalty convex-concave procedure (BCD-PCCP) algorithm is developed to iteratively minimize the channel fitting error across subcarriers. Simulation results validate the proposed approach, determining the maximum effective bandwidth and demonstrating substantial performance improvements. Moreover, for a MIMO OFDM system operating at 28 GHz with 16 subcarriers, the proposed SIM configuration method achieves over 300% enhancement in channel capacity compared to conventional SIM configuration that only accounts for the center frequency.

Stacked Intelligent Metasurface-Enhanced MIMO OFDM Wideband Communication Systems

TL;DR

This work introduces a fully-analog stacked intelligent metasurface (SIM) architecture for wideband MIMO-OFDM that performs beamforming in the electromagnetic wave domain to diagonalize the end-to-end channel and suppress inter-antenna interference. By cascading multiple metasurface layers (L TX-SIM and K RX-SIM), the system creates parallel subchannels and enables fully-analog spatial multiplexing with , reducing baseband processing. The authors formulate a multi-carrier phase-shift optimization problem and solve it with a BCD-PCCP algorithm, achieving near-diagonal end-to-end channels across a finite effective bandwidth (around 20 MHz in their setup) and demonstrating substantial capacity gains (e.g., > over center-frequency configurations at 28 GHz with 16 subcarriers). Compared with fully-digital, hybrid, and DMA-based metasurface approaches, the SIM_MC configuration delivers significant capacity improvements with lower hardware complexity and energy consumption, highlighting its potential for high-capacity, energy-efficient wideband wireless links.

Abstract

Multiple-input multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems rely on digital or hybrid digital and analog designs for beamforming against frequency-selective fading, which suffer from high hardware complexity and energy consumption. To address this, this work introduces a fully-analog stacked intelligent metasurfaces (SIM) architecture that directly performs wave-domain beamforming, enabling diagonalization of the end-to-end channel matrix and inherently eliminating inter-antenna interference (IAI) for MIMO OFDM transmission. By leveraging cascaded programmable metasurface layers, the proposed system establishes multiple parallel subchannels, significantly improving multi-carrier transmission efficiency while reducing hardware complexity. To optimize the SIM phase shift matrices, a block coordinate descent and penalty convex-concave procedure (BCD-PCCP) algorithm is developed to iteratively minimize the channel fitting error across subcarriers. Simulation results validate the proposed approach, determining the maximum effective bandwidth and demonstrating substantial performance improvements. Moreover, for a MIMO OFDM system operating at 28 GHz with 16 subcarriers, the proposed SIM configuration method achieves over 300% enhancement in channel capacity compared to conventional SIM configuration that only accounts for the center frequency.

Paper Structure

This paper contains 18 sections, 1 theorem, 30 equations, 11 figures, 2 tables, 1 algorithm.

Key Result

Lemma 1

By leveraging the matrix vectorization method, the objective function $\mathrm{\Gamma}$ can be transformed into a standard quadratic form w.r.t. w.r.t. $\bm{\phi}^l$ and $\bm{\psi}^k$, respectively, as shown in st.ppp and st.qqq at the top of the next page, where $\mathbf{P}_i = \mathbf{P}_i^\mathbb

Figures (11)

  • Figure 1: The SIM-enhanced wideband MIMO OFDM communication system.
  • Figure 2: The architecture of the SIM.
  • Figure 3: Normalized fitting error $\Omega$ versus system bandwidth $B$, showing the maximum effective bandwidth $B_e$ where interference-free diagonalization is achieved.
  • Figure 4: The per-subcarrier fitting NMSE $\mathcal{S}$ under different $B_e$ setups, where we consider a fixed subcarrier number of $N_e=16$ and varying subcarrier spacing.
  • Figure 5: The channel capacity $C$ versus the number of subcarriers $N_e$ at the fixed optimization bandwidth $B_e = 20$ MHz.
  • ...and 6 more figures

Theorems & Definitions (10)

  • Remark 1
  • Remark 2
  • Remark 3
  • Remark 4
  • Remark 5
  • Remark 6
  • Remark 7
  • Lemma 1
  • proof
  • Remark 8