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Distributed User Scheduling in Multi-Cell MIMO O-RAN with QoS Constraints

Tenghao Cai, Lei Li, Tsung-Hui Chang

Abstract

Distributed scheduling is essential for open radio access network (O-RAN) employing advanced physical-layer techniques such as multi-user MIMO (MU-MIMO), carrier aggregation (CA), and joint transmission (JT). This work investigates the multi-component-carrier (multi-CC) resource block group (RBG) scheduling in MU-MIMO O-RAN with both JT and non-JT users. We formulate a scheduling optimization problem to maximize throughput subject to user-specific quality of service (QoS) requirements while ensuring consistent allocations across cooperating O-RAN radio units (O-RUs) required by JT transmission. The strong variable coupling, non-convexity, and combinatorial complexity make the problem highly challenging. To tackle this, we extend the eigen-based zero-forcing transceiver design to JT users and leverage massive MIMO asymptotic properties to derive a tractable, separable rate approximation. Building on this, we develop two solutions: a centralized block coordinate descent benchmark and a distributed scheduler aligned with the O-RAN architecture. The proposed distributed scheme achieves near-centralized performance with only one round of lightweight coordination among cells, significantly reducing complexity and delay. Extensive simulations validate that our distributed scheduler achieves high scalability, fast convergence, and better QoS satisfaction rate in large-scale MU-MIMO networks.

Distributed User Scheduling in Multi-Cell MIMO O-RAN with QoS Constraints

Abstract

Distributed scheduling is essential for open radio access network (O-RAN) employing advanced physical-layer techniques such as multi-user MIMO (MU-MIMO), carrier aggregation (CA), and joint transmission (JT). This work investigates the multi-component-carrier (multi-CC) resource block group (RBG) scheduling in MU-MIMO O-RAN with both JT and non-JT users. We formulate a scheduling optimization problem to maximize throughput subject to user-specific quality of service (QoS) requirements while ensuring consistent allocations across cooperating O-RAN radio units (O-RUs) required by JT transmission. The strong variable coupling, non-convexity, and combinatorial complexity make the problem highly challenging. To tackle this, we extend the eigen-based zero-forcing transceiver design to JT users and leverage massive MIMO asymptotic properties to derive a tractable, separable rate approximation. Building on this, we develop two solutions: a centralized block coordinate descent benchmark and a distributed scheduler aligned with the O-RAN architecture. The proposed distributed scheme achieves near-centralized performance with only one round of lightweight coordination among cells, significantly reducing complexity and delay. Extensive simulations validate that our distributed scheduler achieves high scalability, fast convergence, and better QoS satisfaction rate in large-scale MU-MIMO networks.

Paper Structure

This paper contains 20 sections, 2 theorems, 45 equations, 9 figures, 2 tables, 2 algorithms.

Table of Contents

  1. Introduction
  2. Related Work
  3. System Model and Problem Formulation
  4. System Model
  5. Transceiver Design Based on EZF
  6. Multi-Dimensional User Scheduling Problem
  7. A Novel Problem Reformulation
  8. Phase 1
  9. Phase 2
  10. Proposed Centralized Algorithm
  11. Distributed Framework and Algorithm Design
  12. Stage 1: Local Optimization at $\text{PU}_1$ to $\text{PU}_M$
  13. Stage 2.1: JT-UE Scheduling Coordination at $\text{PU}_0$
  14. Stage 2.2: NJT-UE QoS Decoupling at $\text{PU}_1$ to $\text{PU}_M$
  15. Stage 3: Refining NJT-UE Scheduling at $\text{PU}_1$ to $\text{PU}_M$
  16. ...and 5 more sections

Key Result

Theorem 1

When the number of transmit antennas is sufficiently large, the rate for NJT-UE $k$ served by cell $m$ associated with RBG $(c,r)$ converges to where ${\psi}_{m,k}^{c,r} \triangleq \log({{({\lambda}}_{k}^{c,r})^2|\mathbf{v}_{m,k}^{c,r} |^2 P}/{\sigma^2})$, ${d}_{m,j,k}^{c,r} \triangleq \log( 1 - \eta_{m,j,k}^{c,r})$, $\eta_{m,j,k}^{c,r} \triangleq { | (\mathbf{v}_{m,j}^{c,r}) ^\mathrm{H}

Figures (9)

  • Figure 1: System Model
  • Figure 2: The interference sources (circled by dashed lines) experienced by JT-UE $i$.
  • Figure 3: Proposed distributed scheduling framework.
  • Figure 4: Information exchange between nodes.
  • Figure 5: Convergence of the proposed centralized scheduling.
  • ...and 4 more figures

Theorems & Definitions (3)

  • Theorem 1
  • proof
  • Theorem 2