Radio Control Optimization for Enhanced QoS-based Spectrum Selection in Heterogeneous 5G Environments with eMBB and uRLLC

Abstract

5G mobile networks provide two main uses: enhanced mobile broadband (eMBB) and ultra-reliable lowlatency communications (uRLLC) are two critical services. While eMBB focuses on maximum data rate, uRLLC prioritizes latency and reliability. However, sharing radio resources between these two use cases creates a complex planning problem due to the trade-off between these different factors. Our proposal introduces an efficient control strategy that optimizes the use of licensed and unlicensed radio resources across various services i.e., eMBB with guaranteed bit rate (eMBB-GBR) and uRLLC ensuring that the traffic requirements of each service are met. The main objective of the proposed control strategy is to maximize the utilization of resources by ensuring the availability of resources, reducing delays, and achieving high throughput. The simulation results clearly show the superiority of the proposed algorithm compared to the reference scheme. This significantly improves the performance of the network by improving the utilization of resources, reducing latency service, increasing the rate of successful packets, and reducing the probability of blocking. The algorithm shows significant improvements, particularly with an 8%, 22%, and 28 % increase in effective capacity for the eMBB-GBR service compared to the reference approaches when the session arrival rate is 1.2. In addition, it significantly reduces the probability of session drops for eMBB-GBR service by about 0.05, 0.12, and 0.17 compared to the reference approaches. Moreover, the proposed control strategy has a significant relative latency for uRLLC service of 13%, 21 %, and 26% compared to reference approaches when URLLC density is around 1000 UEs.

Distributed Reinforcement Learning–based Seamless Multi-Connectivity Solution for Heterogeneous 5GNR and Wi-Fi Networks

“…To tackle these challenges and ensure the reliability of mission-critical services across multiple networks, different solutions have been proposed including spectrum allocation [8,9], capacity management strategies [10,11], and interference control strategies [12,13].…”