JOURNAL ARTICLE

Resource allocation scheme for eMBB and uRLLC coexistence in 6G networks

Muhammed Al-AliElias Yaacoub

Year: 2023 Journal:   Wireless Networks Vol: 29 (6)Pages: 2519-2538   Publisher: Springer Science+Business Media

Abstract

Abstract 5G technology is intended to support three promising services with heterogeneous requirements: Ultra-Reliable and Low Latency Communication (uRLLC), enhanced Mobile Broadband (eMBB), and massive Machine Type Communication (mMTC). 6G is required to support even more challenging scenarios, including the presence of a large number of uRLLC devices, under the massive uRLLC (mURLLC) use case scenario. The presence of these services on the same network creates a challenging task of resource allocation to meet their diverse requirements. Given the critical nature of uRLLC applications, uRLLC traffic will always have the highest priority which causes a negative impact on the performance of other services. In this paper, the problem of uRLLC/eMBB resource allocation is investigated. An optimal resource allocation scheme is proposed with two scenarios including a guaranteed fairness level and minimum data rate among eMBB users. In addition, a knapsack-inspired punctured resource allocation algorithm is proposed where the users’ channel qualities of both services are considered at each time slot leading to the most suitable Resource Block (RB) selection for puncturing in a way that minimizes the negative impact on eMBB performance. The proposed solution was compared with three puncturing baseline reference algorithms and the performance was evaluated in terms of eMBB Sum throughput and Fairness level. The simulation results show that the proposed algorithm outperforms the above-mentioned reference algorithms in all evaluation metrics and is proved to be comparable to the optimal solution given its low complexity.

Keywords:
Computer science Puncturing Resource allocation Knapsack problem Throughput Max-min fairness Resource management (computing) Latency (audio) Computer network Mathematical optimization Distributed computing Algorithm Wireless Telecommunications

Metrics

26
Cited By
4.31
FWCI (Field Weighted Citation Impact)
34
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced Wireless Communication Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Cooperative Communication and Network Coding
Physical Sciences →  Computer Science →  Computer Networks and Communications

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