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Spatial Multiplexing Oriented Channel Reconfiguration in Multi-IRS Aided MIMO Systems

Yuxuan Chen, Qingqing Wu, Guangji Chen, Wen Chen

TL;DR

This work studies spectral-efficiency optimization in a point-to-point MIMO link aided by multiple IRSs. It introduces orthogonal IRS placement to create decoupled sub-channels and employs a two-stage, SCA-based optimization to jointly design IRS elements and transmit power, achieving closed-form beamforming under the placement constraint. The authors prove asymptotic optimality of equal element and power allocation as the total number of elements and the transmit power grow without bound, and they show that SE scales linearly with the number of IRSs, effectively yielding a $K$-fold gain in high-resource regimes. Numerical results confirm significant performance advantages of multi-IRS deployments over a single IRS when resources are ample, and reveal that rank and multiplexing gains improve with more IRSs and elements. Overall, the paper provides practical strategies for deploying and configuring multiple IRSs to harness spatial multiplexing gains in future wireless networks.

Abstract

Spatial multiplexing plays a significant role in improving the capacity of multiple-input multiple-output (MIMO) communication systems. To improve the spectral efficiency (SE) of a point-to-point MIMO system, we exploit the channel reconfiguration capabilities provided by multiple intelligent reflecting surfaces (IRSs) to enhance the spatial multiplexing. Unlike most existing works, we address both the issues of the IRSs placement and elements allocation. To this end, we first introduce an orthogonal placement strategy to mitigate channel correlation, thereby enabling interference-free multi-stream transmission. Subsequently, we propose a successive convex approximation (SCA)-based approach to jointly optimize the IRS elements and power allocation. Our theoretical analysis unveils that equal IRS elements/power allocation scheme becomes asymptotically optimal as the number of IRS elements and transmit power tend to be infinite. Numerical results demonstrate that when the total number of IRS elements or the power exceeds a certain threshold, a multi-IRS assisted system outperforms a single IRS configuration.

Spatial Multiplexing Oriented Channel Reconfiguration in Multi-IRS Aided MIMO Systems

TL;DR

This work studies spectral-efficiency optimization in a point-to-point MIMO link aided by multiple IRSs. It introduces orthogonal IRS placement to create decoupled sub-channels and employs a two-stage, SCA-based optimization to jointly design IRS elements and transmit power, achieving closed-form beamforming under the placement constraint. The authors prove asymptotic optimality of equal element and power allocation as the total number of elements and the transmit power grow without bound, and they show that SE scales linearly with the number of IRSs, effectively yielding a -fold gain in high-resource regimes. Numerical results confirm significant performance advantages of multi-IRS deployments over a single IRS when resources are ample, and reveal that rank and multiplexing gains improve with more IRSs and elements. Overall, the paper provides practical strategies for deploying and configuring multiple IRSs to harness spatial multiplexing gains in future wireless networks.

Abstract

Spatial multiplexing plays a significant role in improving the capacity of multiple-input multiple-output (MIMO) communication systems. To improve the spectral efficiency (SE) of a point-to-point MIMO system, we exploit the channel reconfiguration capabilities provided by multiple intelligent reflecting surfaces (IRSs) to enhance the spatial multiplexing. Unlike most existing works, we address both the issues of the IRSs placement and elements allocation. To this end, we first introduce an orthogonal placement strategy to mitigate channel correlation, thereby enabling interference-free multi-stream transmission. Subsequently, we propose a successive convex approximation (SCA)-based approach to jointly optimize the IRS elements and power allocation. Our theoretical analysis unveils that equal IRS elements/power allocation scheme becomes asymptotically optimal as the number of IRS elements and transmit power tend to be infinite. Numerical results demonstrate that when the total number of IRS elements or the power exceeds a certain threshold, a multi-IRS assisted system outperforms a single IRS configuration.
Paper Structure (10 sections, 4 theorems, 23 equations, 5 figures)

This paper contains 10 sections, 4 theorems, 23 equations, 5 figures.

Table of Contents

  1. Introduction
  2. System Model and Problem Formulation
  3. System Model
  4. Problem Formulation
  5. Proposed Solution
  6. IRS Placement and Beamforming Design
  7. Joint IRS Elements Allocation and Power Optimization
  8. SE Scaling Order Analysis
  9. Numerical Results
  10. Conclusion

Key Result

Proposition 1

When $\chi _1=\chi _2=\chi$, we have $R_2\geqslant R_1$ if

Figures (5)

  • Figure 1: A MIMO wireless communication system aided by $K$ IRSs.
  • Figure 2: Achievable rate versus $M$ under orthogonal placement.
  • Figure 3: Achievable rate versus $P$ under orthogonal placement.
  • Figure 4: Effective rank versus $M$.
  • Figure 5: Elements allocation versus $P$ when $K=3$.

Theorems & Definitions (4)

  • Proposition 1
  • Proposition 2
  • Proposition 3
  • Proposition 4