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SWIPT in Cell-Free Massive MIMO Using Stacked Intelligent Metasurfaces

Thien Duc Hua, Mohammadali Mohammadi, Hien Quoc Ngo, Michail Matthaiou

TL;DR

This work integrates stacked intelligent metasurfaces into a cell-free mMIMO SWIPT framework to markedly enhance energy harvesting without sacrificing information transfer. By deriving closed-form SE expressions for IRs and NL energy metrics for ERs under long-term statistical CSI, the authors formulate and solve a non-convex max-sum-HE problem using a layer-by-layer SIM PS heuristic and a SCA-based power allocation method. The proposed approach yields up to 7x gains in average harvested energy as the number of SIM layers increases and up to about 40% improvements in the minimum SE with power allocation, demonstrating the method's potential for energy-constrained, multiuser wireless networks. These results underscore the practical impact of SIMs for jointly optimizing SWIPT performance in CF mMIMO systems.

Abstract

We investigate the integration of stacked intelligent metasurfaces (SIMs) into cell-free massive multiple input multiple output (CF-mMIMO) system to enhance the simultaneous wireless information and power transfer (SWIPT) performance. Closed-form expressions for the spectral efficiency (SE) of the information-decoding receivers (IRs) and the average sum of harvested energy (sum-HE) at the energy-harvesting receivers (ERs) in the novel system model are derived to subsequently formulate a maximum total average sum-HE problem under a minimum SE threshold per each IR. This problem jointly optimizes the SIM phase-shift (PS) configuration and access points' (APs) power allocation, relying on long-term statistical channel state information (CSI). This non-convex problem is then transformed into more tractable forms. Then, efficient algorithms are proposed, including a layer-by-layer heuristic method for SIMs PS configuration that prioritizes sum-HE for the ERs and a successive convex approximation (SCA)-based power allocation scheme to improve the achievable SE for the IRs. Numerical results show that our proposed algorithms achieve an almost 7-fold sum-HE gain as we increase the number of SIM layers, while the proposed power allocation (PPA) scheme often gains up to 40% in terms of the achievable minimum SE, compared to the equal power allocation.

SWIPT in Cell-Free Massive MIMO Using Stacked Intelligent Metasurfaces

TL;DR

This work integrates stacked intelligent metasurfaces into a cell-free mMIMO SWIPT framework to markedly enhance energy harvesting without sacrificing information transfer. By deriving closed-form SE expressions for IRs and NL energy metrics for ERs under long-term statistical CSI, the authors formulate and solve a non-convex max-sum-HE problem using a layer-by-layer SIM PS heuristic and a SCA-based power allocation method. The proposed approach yields up to 7x gains in average harvested energy as the number of SIM layers increases and up to about 40% improvements in the minimum SE with power allocation, demonstrating the method's potential for energy-constrained, multiuser wireless networks. These results underscore the practical impact of SIMs for jointly optimizing SWIPT performance in CF mMIMO systems.

Abstract

We investigate the integration of stacked intelligent metasurfaces (SIMs) into cell-free massive multiple input multiple output (CF-mMIMO) system to enhance the simultaneous wireless information and power transfer (SWIPT) performance. Closed-form expressions for the spectral efficiency (SE) of the information-decoding receivers (IRs) and the average sum of harvested energy (sum-HE) at the energy-harvesting receivers (ERs) in the novel system model are derived to subsequently formulate a maximum total average sum-HE problem under a minimum SE threshold per each IR. This problem jointly optimizes the SIM phase-shift (PS) configuration and access points' (APs) power allocation, relying on long-term statistical channel state information (CSI). This non-convex problem is then transformed into more tractable forms. Then, efficient algorithms are proposed, including a layer-by-layer heuristic method for SIMs PS configuration that prioritizes sum-HE for the ERs and a successive convex approximation (SCA)-based power allocation scheme to improve the achievable SE for the IRs. Numerical results show that our proposed algorithms achieve an almost 7-fold sum-HE gain as we increase the number of SIM layers, while the proposed power allocation (PPA) scheme often gains up to 40% in terms of the achievable minimum SE, compared to the equal power allocation.

Paper Structure

This paper contains 13 sections, 4 theorems, 38 equations, 3 figures, 2 algorithms.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. Uplink Training and Channel Estimation
  5. Downlink Wireless Information and Power Transmission
  6. Problem Formulation
  7. Proposed Solution
  8. Heuristic Phase Shift Design (Heuristic-PS)
  9. Proposed Power Allocation (PPA) Design
  10. Numerical Results
  11. Conclusion
  12. Useful Derivations for Proposition 2
  13. Proof of Proposition 1

Key Result

Proposition 1

With MRT precoding, the achievable SE of the $k_i$-th IR is given by eq:SEk:Ex, where the effective SINR is where where $\bar{b}_{m, k_i k'_i}$ and $\bar{b}_{m, k_i k_e}$ are defined in Lemma lemma2 (see Appendix A). Moreover,

Figures (3)

  • Figure 1: Impact of SIM layers' number on the sum-HE ($M = 10$, $N = 20$, $S = 25$).
  • Figure 2: Impact of SIM layers' number on the minimum SE ($M = 10$, $N = 20$, $S = 25$).
  • Figure 3: Impact of the PPA design on the minimum SE ($MN = 480$, $S = 25$, $L = 4$).

Theorems & Definitions (6)

  • Proposition 1
  • proof
  • Proposition 2
  • proof
  • Lemma 1
  • Lemma 2