HyRA: A Hybrid Resource Allocation Framework for RAN Slicing

2026-02-18

AI Summary

This work addresses the inefficiency of spectrum utilization in traditional RAN slicing, which relies on dedicated resource reservation to ensure SLA-compliant performance isolation but suffers from poor spectral efficiency under bursty traffic. To overcome this limitation, the authors propose HyRA, a hybrid resource allocation framework that uniquely integrates dedicated resources with a cross-slice shared resource pool. By formulating the problem as a two-stage stochastic optimization model and leveraging sample average approximation, KKT condition analysis, and Big-M encoding, the approach is transformed into a tractable mixed-integer program. A water-filling-based user equipment scheduling algorithm is further designed for practical implementation. Experimental results demonstrate that, across diverse traffic patterns and SLA configurations, HyRA reduces spectrum consumption by 50%–75% compared to purely dedicated or purely shared schemes, effectively balancing strict performance isolation with high resource efficiency.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Machine Learning: Hardware-aware ML

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Search and Retrieval-Augmented AI: Efficiency and scalability of Web search engines
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

The advent of 5G and the emergence of 6G networks demand unprecedented flexibility and efficiency in Radio Access Network (RAN) resource management to satisfy diverse service-level agreements (SLAs). Existing RAN slicing frameworks predominantly rely on per-slice resource reservation, which ensures performance isolation but leads to inefficient utilization, particularly under bursty traffic. We introduce HyRA, a hybrid resource allocation framework for RAN slicing that combines dedicated per-slice allocations with shared resource pooling across slices. HyRA preserves performance isolation while improving resource efficiency by leveraging multiplexing gains in bursty traffic conditions. We formulate this design as a bi-level stochastic optimization problem, where the outer loop determines the dedicated and shared resource budgets and the inner loop performs per-UE scheduling under a novel water-filling approach. By using the sample-average approximation, the Karush-Kuhn-Tucker (KKT) conditions of the inner loop, and Big-M encoding, we transform the problem into a tractable mixed-integer program that standard optimization solvers can solve. Extensive simulations under diverse demand patterns, SLA configurations, and traffic burstiness show that HyRA achieves up to 50-75% spectrum savings compared to dedicated-only and shared-only baselines. These results highlight HyRA as a viable approach for resource-efficient, SLA-compliant RAN slicing in future mobile networks.

Problem

• RAN slicing
• resource allocation
• bursty traffic
• resource efficiency
• SLA compliance

Innovation

• RAN slicing
• hybrid resource allocation
• stochastic optimization
• performance isolation
• resource efficiency