Multiplexing Services in 5G and Beyond: Optimal Resource Allocation Based on Mixed Numerology and Mini-Slots

Abstract

The Fifth Generation (5G) New Radio (NR) Physical Layer (PHY) is designed to successfully address diverse user and service requirements by providing a highly flexible framework. This flexibility is viable through a scalable numerology. Since 5G NR targets to multiplex various applications with different quality of service requirements within the same band, 3rd Generation Partnership Project has introduced a mixed (multi) numerology approach and a mini-slot approach to enhance the adaptability of the PHY. In this contribution, we compare these two approaches focusing on the achievement of low-latency communications. We propose optimization problems that enable to maximize the achievable rate of best effort users, while maintaining latency requirements of low-latency users. Exploiting achievable rate performance as one of the fundamental metrics, we show a comparison of mixed numerology and mini-slot approach in different circumstances. In addition to Cyclic Prefix (CP)-Orthogonal Frequency Division Multiplexing (OFDM), we employ Universal Filtered Multicarrier (UFMC) as a potential beyond 5G technology and show that it achieves an improvement over CP-OFDM. The optimization problems for both mixed numerology and the mini-slot approach are initially given by an integer programming solution. In order to reduce computational complexity for large-scale scenarios, we apply the Dantzig-Wolfe decomposition method, showing that it is possible to achieve the optimal solution with significantly reduced complexity by exploiting the structure of the proposed optimization formulation.

Keywords

• OFDM
• optimal scheduling
• physical layer
• resource management
• scalability
• 5G mobile communication