Degeneracy-Aware Agent-Based Resource Allocation for Multi-User MIMO RSMA Network

TL;DR

This paper introduces a degeneracy-aware, distributed agent-based framework for resource allocation in multi-user MIMO RSMA networks, effectively handling imperfect CSI and residual SIC errors to improve scalability and robustness.

Contribution

It develops a novel degeneracy index and a fixed-point power control mechanism enabling scalable, distributed resource management without requiring global CSI.

Findings

Achieves near-centralized performance in sparse networks.

Provides throughput gains and scalability in dense deployments.

Derives outage probability expressions under practical impairments.

Abstract

This paper proposes a pilot-aware, degeneracy-driven Agent-Based Modelling (ABM) framework for distributed resource allocation in RSMA-enabled multi-user MIMO systems under imperfect Channel State Information (CSI) and residual Successive Interference Cancellation (SIC) error. The centralized RSMA power allocation problem is reformulated as a distributed multi-agent system, where users operate as autonomous agents that iteratively adapt transmit powers based on locally observed feasibility conditions. To capture the joint impact of interference coupling, CSI estimation errors, pilot overhead, and residual SIC error, a novel degeneracy index defined as the ratio of target to achieved signal-to-interference-plus-noise ratio (SINR) is introduced as a unified feasibility metric. This enables a scalable fixed-point power control mechanism that characterizes the feasible operating region without requiring global CSI. Analytical expressions for user-level and system-level outage probabilities are derived under spatially correlated fading, providing insights into reliability under practical impairments. The fundamental interplay between degeneracy, outage probability, and effective throughput is established, revealing that system performance is governed by the feasibility of the bottleneck user. To further enhance resilience, Degeneracy-Weighted Path Robustness (DWPR) and Functional Substitution Score (FSS) are incorporated to exploit path diversity and functional redundancy. Numerical results show that the proposed framework achieves near-centralized performance in sparse networks, while providing notable throughput gains and improved scalability in dense deployments, highlighting its effectiveness for robust and distributed resource management in next-generation wireless systems.