# DORA: Dynamic O-RAN Resource Allocation for Multi-Slice 5G Networks

arXiv: https://arxiv.org/abs/2509.07242 · HTML: https://mlsanity.com/paper/2509.07242/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 8 Sep 2025.

## Built on by (most cited first, 2 of 2)

- [ORAN-DEFEND: Subspace Detection and Sanitization of Backdoor DRL xApps in Open RAN](https://mlsanity.com/paper/2607.06647/) (2026)
- [Evolving Inspectable O-RAN Slicing xApps with LLMs](https://mlsanity.com/paper/2609.27337/) (2026)

## Abstract (arXiv)

The fifth generation (5G) of wireless networks must simultaneously support heterogeneous service categories, including Ultra-Reliable Low-Latency Communications (URLLC), enhanced Mobile Broadband (eMBB), and massive Machine-Type Communications (mMTC), each with distinct Quality of Service (QoS) requirements. Meeting these demands under limited spectrum resources requires adaptive and standards-compliant radio resource management. We present DORA (Dynamic O-RAN Resource Allocation), a deep reinforcement learning (DRL) framework for dynamic slice-level Physical Resource Block (PRB) allocation in Open RAN. DORA employs a PPO-based RL agent to allocate PRBs across URLLC, eMBB, and mMTC slices based on observed traffic demands and channel conditions. Intra-slice PRB scheduling is handled deterministically via round-robin among active UEs, simplifying control complexity and improving training stability. Unlike prior work, DORA supports online training and adapts continuously to evolving traffic patterns and cross-slice contention. Implemented in the standards-compliant OpenAirInterface (OAI) RAN stack and designed for deployment as an O-RAN xApp, DORA integrates seamlessly with RAN Intelligent Controllers (RICs). Extensive evaluation under congested regimes shows that DORA outperforms three non-learning baselines and a textttDQN agent, achieving lower URLLC latency, higher eMBB throughput with fewer SLA violations, and broader mMTC coverage without starving high-priority slices. To our knowledge, this is the first fully online DRL framework for adaptive, slice-aware PRB allocation in O-RAN.