# Practical Performance Analysis of Interference in DSS System
## 6 Discussion  
In this paper, all results are based on commercially available DSS networks. First, we study the basic architecture of DSS. Then, the theoretical analysis of DSS interference is carried out, and two achievable interference mitigation solutions are innovatively proposed: buffer setting and rate matching. Through theoretical analysis, we found that the NR of the DSS cell will be seriously interfered by the LTE of neighbor DSS, and its performance will be reduced by up to 56%. Setting the buffer can improve the downlink performance of NR of DSS cell by 40-60%; after adopting the CRS rate-matching solution, the downlink performance of NR can be increased by about 60%.  
The realistic test environment for this study was built for the first time on a commercial 4G/5G coexistence network, which is unprecedented for DSS interference analysis. Compared with the interference between other inter-systems, most of NR of the DSS cell is strongly interfered by the LTE signal of the neighbor DSS cell. To address this issue, we conducted field tests of buffer setting and rate matching. It has been verified that the buffer setting solution and the rate-matching solution can effectively reduce the intra-frequency interference between the inter-system. The buffer setting solution can improve the performance of the interfered cell by an average of 60%, but down to 10%. Therefore, the performance improvement of this solution is not stable. The rate-matching solution can also improve the performance of the interfered cell by an average of 60%. This is consistent with the conclusion of the theoretical analysis.  
From theoretical and practical analysis, it can be verified that the buffer setting solution can effectively mitigate interference, improve network speed, and be deployed easily.  
Figure 20: LTE to NR Downlink Interference Test Results after Rate Matching.  
However, unstable performance improvement and network instability may occur. The rate-matching solution can stably increase the network rate by about 60%. The improvement effect is obvious. However, it will bring a certain resource overhead, and there is a risk that the software upgrade will be relatively slow. The operators can choose a solution on demand based on existing networks.  
Although we selected commercial test scenarios, we lack traversing all scenarios of loads and user behaviors, and the test environment and scenarios are relatively simple; so, research in this paper is not complete and we can further improve and continue our research. The future work includes studying DSS to integrate more network frequency bands, such as satellite, millimeter wave, etc. Meanwhile, since the implementation of DSS triggers resource wastage, further attempts can be made in the future on how to save spectrum resources. Further, we will consider the DSS interference in inter-systems, and consider integrating AI algorithms and SDN architecture on the basis of DSS to improve network quality more intelligently.  
Conceptualization, W.X. and C.H.; methodology, W.X. and C.H.; validation, M.W. and X.L.; formal analysis, M.W.; investigation, M.W.; resources, M.W.; data curation, M.W. and X.L.; writing--original draft preparation, M.W.; writing--review and editing, M.W. and X.L.; supervision, W.X. and C.H.; project administration, C.H.; funding acquisition, W.X. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the major research project of China Telecom \"5G wireless enhancement technology research and experiment\". Grant ID: 22 HQBYYF0048-001.  
Not applicable.