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STARS-Enabled Full-Duplex Two-Way mMIMO System Under Spatially-Correlated Channels

Anastasios Papazafeiropoulos, Pandelis Kourtessis, Symeon Chatzinotas, Dimitra I. Kaklamani, Iakovos S. Venieris

TL;DR

This work tackles STARS-enabled full-duplex two-way mMIMO under spatially correlated Rayleigh fading and imperfect CSI. It develops UaTF-based closed-form average UL and DL SE expressions that depend only on large-scale statistics, and proposes a low-complexity ProGrAM algorithm to optimize STARS passive beamforming with an ES protocol. MMSE channel estimation is employed with single-phase training to reduce overhead, enabling PBM design over longer coherence intervals. Numerical results show that the STARS-enabled FD system achieves superior sum SE compared to STARS-enabled HD and cRIS-enabled FD systems, with the performance improving as the STARS size grows and decreasing with higher STARS correlation. The approach offers practical gains in coverage and spectral efficiency for next-generation wireless networks, and points to future work on adaptive power allocation and broader parameter studies.

Abstract

\underline{S}imultaneous \underline{t}ransmitting \underline{a}nd \underline{r}eflecting \underline{s}urface (STARS)-assisted systems have emerged to fill this gap by providing $ 360^{\circ}$ wireless coverage. In parallel, full-duplex (FD) communication offers a higher achievable rate through efficient spectrum utilization compared to the half-duplex (HD) counterpart. Moreover, two-way/bi-directional communications in an FD system can further enhance the system's spectral efficiency. Hence, in this paper, we propose a STARS-enabled massive MIMO deployment in an FD two-way communication network for highly efficient spectrum utilization, while covering the dead zones around the STARS. This model enables simultaneous information exchange between multiple nodes, while \emph{potentially} doubling the spectral efficiency (SE). By invoking the use-and-then-forget (UaTF) combining scheme, we derive a closed-form expression for an achievable SE at each user of the system considering both uplink and downlink communications based on statistical channel state information (CSI), while also accounting for imperfect CSI and correlated fading conditions. Moreover, we formulate an optimization problem to obtain an optimal passive beamforming matrix design at the STARS that maximizes the sum achievable SE. The considered problem is non-convex and we propose a provably-convergent low-complexity algorithm, termed as \underline{pro}jected \underline{gr}adient \underline{a}scent \underline{m}ethod (ProGrAM), to obtain a stationary solution. Extensive numerical results are provided to establish the performance superiority of the FD STARS-enabled system over the HD STARS-enabled and FD conventional RIS (cRIS)-enabled counterparts, and also to show the effect of different parameters of interest on the system performance.

STARS-Enabled Full-Duplex Two-Way mMIMO System Under Spatially-Correlated Channels

TL;DR

This work tackles STARS-enabled full-duplex two-way mMIMO under spatially correlated Rayleigh fading and imperfect CSI. It develops UaTF-based closed-form average UL and DL SE expressions that depend only on large-scale statistics, and proposes a low-complexity ProGrAM algorithm to optimize STARS passive beamforming with an ES protocol. MMSE channel estimation is employed with single-phase training to reduce overhead, enabling PBM design over longer coherence intervals. Numerical results show that the STARS-enabled FD system achieves superior sum SE compared to STARS-enabled HD and cRIS-enabled FD systems, with the performance improving as the STARS size grows and decreasing with higher STARS correlation. The approach offers practical gains in coverage and spectral efficiency for next-generation wireless networks, and points to future work on adaptive power allocation and broader parameter studies.

Abstract

\underline{S}imultaneous \underline{t}ransmitting \underline{a}nd \underline{r}eflecting \underline{s}urface (STARS)-assisted systems have emerged to fill this gap by providing wireless coverage. In parallel, full-duplex (FD) communication offers a higher achievable rate through efficient spectrum utilization compared to the half-duplex (HD) counterpart. Moreover, two-way/bi-directional communications in an FD system can further enhance the system's spectral efficiency. Hence, in this paper, we propose a STARS-enabled massive MIMO deployment in an FD two-way communication network for highly efficient spectrum utilization, while covering the dead zones around the STARS. This model enables simultaneous information exchange between multiple nodes, while \emph{potentially} doubling the spectral efficiency (SE). By invoking the use-and-then-forget (UaTF) combining scheme, we derive a closed-form expression for an achievable SE at each user of the system considering both uplink and downlink communications based on statistical channel state information (CSI), while also accounting for imperfect CSI and correlated fading conditions. Moreover, we formulate an optimization problem to obtain an optimal passive beamforming matrix design at the STARS that maximizes the sum achievable SE. The considered problem is non-convex and we propose a provably-convergent low-complexity algorithm, termed as \underline{pro}jected \underline{gr}adient \underline{a}scent \underline{m}ethod (ProGrAM), to obtain a stationary solution. Extensive numerical results are provided to establish the performance superiority of the FD STARS-enabled system over the HD STARS-enabled and FD conventional RIS (cRIS)-enabled counterparts, and also to show the effect of different parameters of interest on the system performance.

Paper Structure

This paper contains 15 sections, 5 theorems, 59 equations, 12 figures, 1 algorithm.

Table of Contents

  1. Introduction
  2. System Model
  3. Channel Model
  4. Signal Transmission and Reception
  5. Channel Estimation
  6. Problem Formulation
  7. Average Uplink SE
  8. Average Downlink SE
  9. Problem Formulation to Maximize the Sum SE
  10. Proposed Solution
  11. Numerical Results and Discussion
  12. Conclusion
  13. Proof of Theorem \ref{['thm:UL-SINR']}
  14. Proof of Theorem \ref{['thm:DL-SINR']}
  15. Proof of Theorem \ref{['thm:gradClosed']}

Key Result

Proposition 1

The MMSE estimate of the UL cascaded channel $\tilde{\mathbf{u}}_{k}$ is given by where and $\tilde{\mathbf{r}}_{k}$, given by train2, is the noisy observation of $\tilde{\mathbf{u}}_k$.

Figures (12)

  • Figure 1: A STARS-Enabled FD two-way mMIMO system with multiple UEs in transmission and reflection regions.
  • Figure 2: A coherence interval.
  • Figure 3: Simulation setup
  • Figure 4: Impact of random initial points ($\boldsymbol{\theta}_{\mathrm r}^{(0)}, \boldsymbol{\theta}_{\mathrm t}^{(0)}$) on the convergence of the proposed ProGrAM.
  • Figure 5: Impact of the number of STARS elements on the average sum SE.
  • ...and 7 more figures

Theorems & Definitions (6)

  • Proposition 1
  • Proposition 2
  • Remark 1
  • Theorem 1
  • Theorem 2
  • Theorem 3