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Harnessing Stacked Intelligent Metasurface for Enhanced Cell-Free Massive MIMO Systems: A Low-Power and Cost Approach

Enyu Shi, Jiayi Zhang, Yiyang Zhu, Jiancheng An, Chau Yuen, Bo Ai

TL;DR

The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs.

Abstract

In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems to enhance access point (AP) capabilities and address high power consumption and cost challenges. Specifically, we investigate the uplink performance of a SIM-enhanced CF mMIMO system and propose a novel system framework. First, the closed-form expressions of the spectral efficiency (SE) are obtained using the unique two-layer signal processing framework of CF mMIMO systems. Second, to mitigate inter-user interference, an interference-based greedy algorithm for pilot allocation is introduced. Third, a wave-based beamforming algorithm for SIM is proposed, based only on statistical channel state information, which effectively reduces the fronthaul costs. Finally, a max-min SE power control algorithm is proposed to improve the performance of UE with inferior channel conditions. The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs. In particular, the best SE performance is achieved with the deployment of 20 APs plus 1200 SIM meta-atoms. Finally, the proposed wave-based beamforming algorithm can enhance the SE performance of SIM-enhanced CF-mMIMO systems by 57\%, significantly outperforming traditional CF mMIMO systems.

Harnessing Stacked Intelligent Metasurface for Enhanced Cell-Free Massive MIMO Systems: A Low-Power and Cost Approach

TL;DR

The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs.

Abstract

In this paper, we explore the integration of low-power, low-cost stacked intelligent metasurfaces (SIM) into cell-free (CF) massive multiple-input multiple-output (mMIMO) systems to enhance access point (AP) capabilities and address high power consumption and cost challenges. Specifically, we investigate the uplink performance of a SIM-enhanced CF mMIMO system and propose a novel system framework. First, the closed-form expressions of the spectral efficiency (SE) are obtained using the unique two-layer signal processing framework of CF mMIMO systems. Second, to mitigate inter-user interference, an interference-based greedy algorithm for pilot allocation is introduced. Third, a wave-based beamforming algorithm for SIM is proposed, based only on statistical channel state information, which effectively reduces the fronthaul costs. Finally, a max-min SE power control algorithm is proposed to improve the performance of UE with inferior channel conditions. The results indicate that increasing the number of SIM layers and meta-atoms leads to significant performance improvements and allows for a reduction in the number of APs and AP antennas, thus lowering the costs. In particular, the best SE performance is achieved with the deployment of 20 APs plus 1200 SIM meta-atoms. Finally, the proposed wave-based beamforming algorithm can enhance the SE performance of SIM-enhanced CF-mMIMO systems by 57\%, significantly outperforming traditional CF mMIMO systems.
Paper Structure (19 sections, 1 theorem, 34 equations, 11 figures, 1 table, 3 algorithms)

This paper contains 19 sections, 1 theorem, 34 equations, 11 figures, 1 table, 3 algorithms.

Table of Contents

  1. Introduction
  2. SIM-enhanced CF mMIMO System Model
  3. Channel Model
  4. Uplink Pilot Training and Channel Estimation
  5. Uplink Data Transmission
  6. Closed-form Expressions and Performance Analysis
  7. Large Scale Fading Decoding (LSFD)
  8. Equal Gain Combining Decoding (EGCD)
  9. System Optimization and Design
  10. Pilot Allocation
  11. SIM Wave-based Beamforming Design
  12. Power Control Design
  13. Numerical Results and Discussion
  14. Simulation Setup
  15. Impact of Parameters in CF mMIMO Systems
  16. ...and 4 more sections

Key Result

Theorem 1

The closed-form expression for the uplink SE of UE $k$ can be expressed by SE_k, where the SINR with MR combining and LSFD is given by SINR_k_close at the top of this page. Specifically, the desired signal is denoted by the following formula where ${\bf{\bar{h}}}_{l,k}^{} = {\bf{W}}_{l,1}^{\rm{H}}{\bf{G}}_l^{\rm{H}}{\bf{\bar{h}}}_{{\rm{SI}}{{\rm{M}}_l},k}$. Moreover, the definition of non-coheren

Figures (11)

  • Figure 1: Illustration of CF mMIMO and SIM-enhanced CF mMIMO systems. (a) Illustration of the CF mMIMO system. (b) Illustration of the SIM-enhanced CF mMIMO system and the SIM architecture for AP $l$.
  • Figure 2: Average SE per UE against different numbers of APs under EGCD/LSFD with AP full power transmission ($M = 5$, $N = 64$, $K = 5$, $U = 2$, $\tau_p = 4$, ${d_x} = {d_y} = {1 \mathord{\left/ {\newline} \right. \nulldelimiterspace} 2}\lambda$).
  • Figure 3: Average SE per UE against different numbers of APs with the total number of meta-atoms $N_{\rm{total}} = 1200$ on all SIM-enhanced APs over EGCD/LSFD with AP full power transmission ($M = 5$, $K = 5$, $U = 1$, $\tau_p = 4$, ${d_x} = {d_y} = {1 \mathord{\left/ {\newline} \right. \nulldelimiterspace} 2}\lambda$).
  • Figure 4: Average SE per UE against different numbers of AP antennas over EGCD/LSFD with AP full power transmission ($L = 10$, $M = 5$, $N = 25$, $K = 5$, $\tau_p = 4$, ${d_x} = {d_y} = {1 \mathord{\left/ {\newline} \right. \nulldelimiterspace} 2}\lambda$).
  • Figure 5: Heatmap of average SE per UE against different numbers of AP antennas and SIM meta-atoms per layer over LSFD and wave-based beamforming optimization with AP full power transmission ($L = 10$, $M = 5$, $K = 5$, $\tau_p = 4$, ${d_x} = {d_y} = {1 \mathord{\left/ {\newline} \right. \nulldelimiterspace} 2}\lambda$).
  • ...and 6 more figures

Theorems & Definitions (6)

  • Remark 1
  • Remark 2
  • Theorem 1
  • Remark 3
  • Remark 4
  • Remark 5