A quality-of-service-centric uplink rate-splitting approach for next-generation multiple access

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Date

2025-06

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IEEE

Abstract

Recently, Rate-Splitting Multiple Access (RSMA) has emerged as a powerful paradigm for meeting the demanding performance requirements of 6G wireless networks through non-orthogonal high-rate data transmission. However, uplink access in RSMA necessitates optimizing the decoding order, which can lead to significant search latency. Besides, the process overlooks the Quality-of-Service (QoS) constraints of different traffic types, making current RSMA methods inadequate, especially for low-latency communication. Here, we address this issue by proposing QORA, short for QoS-aware One-shot Rate-splitting multiple Access, a multi-agent Deep Q-Network (DQN) framework that leverages a novel QoS-aware transmit power allocation and decoding order policy in uplink RSMA that achieves remarkable performance improvements while maintaining low latency and high admission rates.

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EEE, Random access, RSMA, Uplink power allocation, User admission policy, Deep learning

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