RAN Slicing With Joint Resource Allocation for a Multi-Tenant-Multi-Service System

• Published in: IEEE transactions on cognitive communications and networking Vol. 11; no. 3; pp. 1927 - 1939
• Main Authors: Tul Muntaha, Sidra, Hafeez, Maryam, Ahmed, Qasim Z., Khan, Faheem A., Zaharis, Zaharias D., Lazaridis, Pavlos I.
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.06.2025; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G mobile communication; Bandwidth; Combinatorial analysis; Complexity; Computation; eMBB; Interference; Mixed integer; mMTC; MTMS; Network slicing; NOMA; Optimization; Polynomials; Provisioning; Quality of service; RAN slicing; Resource allocation; Resource management; Search algorithms; Spectral efficiency; Subcarriers; Thresholds; Ultra reliable low latency communication; URLLC; Virtual networks
• ISSN: 2332-7731; 2372-2045; 2332-7731
• DOI: 10.1109/TCCN.2024.3490781

In Multi-Tenant Multi-Service (MTMS) systems, multiple Mobile Virtual Network Operators (MVNOs) share the same physical network infrastructure, with each tenant provisioning a variety of 5G network slices with distinct service needs. Efficient resource allocation enhances utilization. This paper analyses System Spectral Efficiency (SSE) of a downlink MTMS system with three types of network slices. The SSE maximization problem involves joint resource allocation (subcarrier and power) optimization, formulated as a combinatorial Mixed-Integer Non-linear Program (MINLP). Solving such NP-hard problems optimally within a reasonable time is challenging. This research improves SSE by meeting slice performance thresholds and reducing computation times. To address this, we propose Joint Power and Subcarrier Allocation (JPSA) using a population-based natural search algorithm with polynomial time complexity, which is compared with Bounded Exhaustive Search (BES) having exponential time complexity. Both schemes result in sub-optimal and nearly equivalent solutions, but JPSA outperforms BES with much reduced computation time. Additionally, we compare JPSA with Equal Power and Subcarrier Optimization (EPSO) and Equal Subcarrier and Power Optimization (ESPO), demonstrating a 5% and 6% SSE improvement compared to EPSO and ESPO, respectively. The JPSA model is analysed through simulations, considering BS transmit power, slice QoS thresholds, user count, and intra-slice interference threshold.