# eMBB-URLLC Resource Slicing: A Risk-Sensitive Approach

## TL;DR

This paper introduces a risk-sensitive resource allocation method for 5G URLLC and eMBB traffic, balancing reliability and minimizing impact on eMBB users using CVaR and chance constraints.

## Contribution

It proposes a novel risk-sensitive formulation using CVaR and chance constraints for resource slicing between URLLC and eMBB in 5G networks.

## Key findings

- Efficient resource allocation for URLLC with minimal eMBB disruption.
- Guarantees high reliability for both URLLC and eMBB traffic.
- Convex optimization approach ensures convergence and practical implementation.

## Abstract

Ultra Reliable Low Latency Communication (URLLC) is a 5G New Radio (NR) application that requires strict reliability and latency. URLLC traffic is usually scheduled on top of the ongoing enhanced Mobile Broadband (eMBB) transmissions (i.e., puncturing the current eMBB transmission) and cannot be queued due to its hard latency requirements. In this letter, we propose a risk-sensitive based formulation to allocate resources to the incoming URLLC traffic while minimizing the risk of the eMBB transmission (i.e., protecting the eMBB users with low data rate) and ensuring URLLC reliability. Specifically, the Conditional Value at Risk (CVaR) is introduced as a risk measure for eMBB transmission. Moreover, the reliability constraint of URLLC is formulated as a chance constraint and relaxed based on Markov's inequality. We decompose the formulated problem into two subproblems in order to transform it into a convex form and then alternatively solve them until convergence. Simulation results show that the proposed approach allocates resources to the incoming URLLC traffic efficiently while satisfying the reliability of both eMBB and URLLC.