An Rate Adjustment Algorithm for Scalable URLLC in Beyond 5G Networks

Ultra-reliable low latency communications (URLLC) service class introduced in Fifth Generation (5G) New Radio (NR) caters to mission-critical applications with stringent quality of service requirements. Meeting such demanding design goals require a paradigm shift in resource management procedures. Conventional reactive schemes need to be replaced by novel and proactive resource management schemes that can efficiently meet such demanding design targets. In this paper, we propose a novel location-aware transmission rate adjustment scheduling procedure for URLLC networks based on a predictive interference management scheme. Prior to scheduling, a geographical relocation of some of the receivers, which cannot overcome a minimum reliability/outage requirement set by physical layer, is enforced if the corresponding long term channel and interference statistics fail to meet a proposed criteria. Extensive system level simulations show that the proposed relocation and interference prediction based scheduling method meets the reliability constraint and enhances utilization factor of the scalable URLLC network resource significantly. The proposed scheme demonstrates around an order of magnitude lower outage probability compared to a baseline conventional scheme, while having a higher resource efficiency.