# Optimized DM-RS Configuration for Improved 5G New Radio Network Capacity and Performance.
## 2 Related Work  
DM-RS signals were introduced with 5G NR systems for the first time; standardization was performed under 3 GPP specifications [3] and explained further in the literature [4; 5; 6]. During the standardization process, the comparative performance of different DM-RS patterns was analyzed, with a focus on throughput and block error rate (BLER) performance in [7] and spectral efficiency and frame error rate (FER) performance in [8] for different configuration and mobility scenarios. Clearly, in the early stages, the main goal was to secure system stability, and the research approach was to design the system for the worst-case scenario, which is reflected in simulations as very high terminal speed assumptions and deployment of the shortest possible SCS (15 kHz) are considered.  
A group of papers is dedicated to system design and in particular numerology, frame structure, reference signals, multi-antenna schemes, cell-search and random-access procedures to support high-speed mobility use cases, with a focus on high-speed trains [9; 10; 11]. Another group of papers [12; 13; 14] has a similar focus, with the only difference being that some non-terrestrial-network use cases are covered, along with V2X communication with a focus on the design of sidelink. When it comes to reference signal design, the main research direction in these papers is an increase in resource allocation for DM-RS symbols, which enables better channel estimation and network performance for fast-moving terminals. Different metrics are used for benefit assessment; however, in all these papers, the research trend is to address the most challenging use cases, which remain uncommon after several years of commercial deployment of 5G/NR networks, while the opposite direction and reduction in reference signals for better spectral efficiency have not been tackled so far.  
Not directly related to DM-RS configuration, but still relevant to the overall picture, is research work conducted in the domain of Doppler effects and modeling, focusing on the analysis of coherence time distribution in [15] and Doppler estimation error performance in [16]. Another domain of research is the application of tools from the artificial intelligence and machine learning (AI/ML) domain in system design, with a focus on channel estimation enhancements [17] while a deep learning-based adaptive DM-RS configuration framework was investigated in [18].  
The focus of the research discussed in this paper is an investigation of the negative effects of increased resource allocation for DM-RS and an assessment of use cases where DM-RS may be optimized for improved capacity and better user experience, based on Doppler effects assessment modeled for various configurations and use cases. To the best of our knowledge, there is not much research in this direction with such a systematic approach. In addition to the aforementioned novelty, an important contribution of this research is the implementation of different configurations in commercial networks for various use cases, with a systematic review and deep-dive analysis of the impact of system design on different aspects of network performance and connection quality, based on real measurements in the field.