Research on the scheme of identifying 5G indoor and outdoor co-channel interference based on 4G data
5G indoor and outdoor networks are based on the 100MHz bandwidth of the 2.6GHz frequency band, which is a co-frequency network. Field test data show that in the case of 5G indoor and outdoor co-frequency networking, outdoor co-frequency strong interference signals have a greater impact on indoor cells. As can be seen from Figure 1 and Figure 2, when the indoor level is higher than the outdoor level by more than 5dB, the download rate loss of the indoor cell is generally lower than 15%; when the indoor level is lower than the outdoor level by more than 5dB, the outdoor interference will affect the room. The maximum performance impact of sub-download rate can reach 45%.
However, at this stage, there are few 5G network users, the MR function of the main equipment supplier 5G network management has not been fully enabled, and the on-site test and evaluation method is expensive. Both existing methods cannot currently support the identification of 5G outdoor strong interference cells.
According to the current network characteristics of 4G and 5G co-antenna construction, and based on the MR data of the FDD1800 anchor 4G cell that shares RRU with the 5G indoor sub-cell as the benchmark, the indoor and outdoor 5G cell levels can be estimated separately, and the indoor and outdoor 5G levels can be estimated according to the indoor and outdoor 5G levels. Poor ratio to identify outdoor 5G strong co-channel interference cells.
This paper proposes a technical solution to quickly identify 5G outdoor high-interference co-frequency cells based on 4G network measurement report data. The field test results are in line with theoretical expectations, which proves that in the early stage of 5G coverage, the above-mentioned 5G outdoor co-channel interference source identification can be used. technology, and efficiently discover 5G co-frequency high-interference cells. This solution avoids a lot of on-site inspection and coordination work, and can carry out network pre-optimization work in advance before the 5G network load increases.
