# Optimized DM-RS Configuration for Improved 5G New Radio Network Capacity and Performance.
## 5 DM-RS Optimization, Achieved Network Capacity and Performance Improvements
### DM-RS Optimization for FWA Use Case and Improved Capacity  
As discussed earlier, a DM-RS optimization campaign was conducted in a 5G NR network that serves both FWA and MBB use cases, where the data payload generated by the FWA use case is dominant, while the MBB use case is served in parallel but with significantly lower data payloads. 5G/NR is configured over two channels, on different frequencies (3.5 GHz and 2600 MHz) and with different bandwidths (100 MHz and 40 MHz, respectively). The initial DM-RS configuration had the following parameter values: dmrs-Type = 1, dmrs-maxLength = 2, dmrs-AdditionalPosition = 1. Optimization of DM-RS was executed on a group of heavily loaded sites, with very high physical resource block (PRB) utilization, reaching values above 70% during busy hours. The main goal of the optimization activity was to achieve capacity improvements in a heavily loaded network, reduce PRB utilization for the same payload and release some PRBs through overhead reduction so additional traffic could be served. Optimization measures included a decrease in the parameter dmrs-maxLength to a value of 1 and a change in dmrs-AdditionalPosition configuration from two symbols to adaptive configuration, allowing the scheduler to decide if a second symbol is needed or not, based on parameters of the connection. As the dominant use case in the observed network is FWA, with users with limited mobility, the impact of optimization measures was tested mainly through an analysis of key performance indicators (KPIs) obtained from the 5G/NR performance management (PM) system. The focus was on KPIs that measure data payload, amount of data transferred through the network; resource utilization, average PRB occupancy in time; and spectral efficiency, measured as achieved throughput per resource block, calculated as a ratio between data payload in a cell and the average number of used PRBs. All KPI measurements were based on counters collected from the PM system on the cell level, with a granularity period of 1h. The analysis focused on performance comparison during periods of one week before and after the changes were implemented. In addition, a longer period was observed, with a focus on network performance during the first week of three consecutive months, with initial settings deployed during the first month and optimized settings tested in the second and third months. Figure 6 presents spectral efficiency and PRB utilization one week before and one week after the parameter change was implemented. Before a deep-dive analysis of spectral efficiency, it is worth mentioning that it is a metric that is highly correlated with traffic patterns and data payload. Typically, higher spectral efficiency values are achieved for heavy traffic use cases like FTP or video streaming, while lower spectral efficiency is achieved for bursty traffic like messaging, where the buffer is not full, and the full potential of 4G/LTE or 5G/NR radio interface may not be utilized. For that reason, the data payload is presented in parallel in the lower part of Figure 6a. Weekend days are highlighted since slightly different traffic patterns and higher data payload may be observed compared to the Monday-Friday period. In a comparison of two weeks, it was found that an improvement of spectral efficiency of approximately 5% was achieved in the second week with optimized settings. Figure 6b presents changes in PRB utilization with hourly resolution. Focusing on busy hours during the day with approximately similar data payload, a decrease in PRB usage of approximately 5-8% may be observed, which is in line with expectations. Figure 6 clearly shows improvements in spectral efficiency and a decrease in PRB utilization, but also a high level of correlation between observed metrics and traffic patterns. For that reason, the impact of DM-RS parameter changes was observed during a longer period, to avoid the impact of traffic pattern changes that typically happen during the month.