Reliability enhancement in multi-numerology-based 5G new radio using INI-aware scheduling

Abstract

Multi-numerology waveform-based 5G new radio (NR) systems offer great flexibility for different requirements of users and services. However, there is a new type of problem that is defined as inter-numerology interference (INI) between multiple numerologies. This paper proposes novel scheduling and resource allocation techniques to enhance the overall reliability and also provide extra protection for ultra-reliable and low-latency communications (uRLLC) users and cell edge users against INI. Proposed methods are useful for Internet of Things (IoT) communications, and they do not cause additional spectral usage, computational complexity, and latency. Practical INI-aware schemes in this paper include fractional numerology domain (FND) scheduling, power difference-based (PDB) scheduling, and machine learning-based (MLB) scheduling algorithms. INI and signal-to-interference ratio (SIR) results for multi-numerology systems are obtained through computer simulations to show trade-offs between different scenarios and success of the proposed algorithms.