当前4G网络商用已久，5G SA网络也趋于成熟，但LTE终端仍大量被用户所持有。这是因为部分鸿蒙系统的华为高端手机因美国芯片制裁方案的施压，硬件上不支持5G。同时，农村及偏远郊区LTE网络覆盖优于5G网络，大量用户仍热衷于价格低廉的4G终端。最后，部分区域的通信运营商通过4G网络承载用户的数据和语音业务以节省5G建网投资成本。因此，4/5G网络长期共存这一趋势暂时无法改变，所以研究4/5G双模网络协同的优化，打造一张覆盖良好、容量均衡、用户满意度高的精品移动网络迫在眉睫，具有重大现实意义。

在研究国内外4/5G网络现状和协同优化技术的基础上，本文结合某电信运营商4/5G网络协同优化项目实际情况，通过大量走访用户频繁投诉的网络问题痛点，使用网管控制平台（ElasticNet）提取并计算异常网络KPI指标，以覆盖和容量两大层面网络问题作为判决依据，运用MapInfor或Google earth等工具导入基站工参制作出扇区覆盖图层以便提前预判好每个小区覆盖半径、天线的方位角和下倾角等基本信息，划分好待优化区域，并确立优化目标；进而准备好数据采集所需的车辆、GPS、终端设备和鼎力Pioneer测试软件，进行CQT或DT数据的采集。围绕着“覆盖”和“容量”两大层面网络问题，结合KPI异常指标，使用Pioneer对现场实采的log日志进行信令解析，基于协同优化门限参数设置模型，分析并设计出最优4/5G 协同优化方案，并按照优化的优先级高低顺序逐步解决网络中存在的问题。随后与客户共同商讨，改进优化方案中存在的漏洞，确保优化方案更加合理。紧接着对优化方案加以实施，逐项完成优化任务。最后，将优化前后结果加以对比，不断改进优化方案以达到预期优化目标，完成优化报告的撰写并分享优化成果。

针对覆盖层面5G边缘弱覆盖区域、容量层面LTE高负荷区域的网络问题，通过4/5G网络协同优化方案实施，让覆盖层面的5G平均SS-RSRP(Synchronization Signal Reference Signal Received Power)由-109.3dbm提升至-103.5dbm ，提升了5.6%；同时，在容量层面，5G 25个SA小区下行 PRB平均利用率提升了 19.05%。由此可见LTE网络负荷大大降低，使得5G SA网络在一定程度上分流了4G网络的容量压力，容量负载均衡效果明显。因此，通过4/5G网络协同优化，验证了本文提出的4/5G网络协同优化方案设计的可行性，为后续4/5G网络协同优化提供了一定的思路参考和借鉴。

The current 4G network has been commercialized for a long time, and the 5G SA network is also maturing, but LTE terminals are still widely held by users. This is because some Huawei high-end smartphones of the HarmonyOS system do not support 5G in hardware due to pressure from the US chip sanctions program. Meanwhile, LTE networks in rural and remote suburbs have better coverage than 5G networks, and a large number of users are still enthusiastic about low-priced 4G terminals. Finally, some communication operators in certain regions carry user data and voice services through 4G networks to save investment costs in 5G network construction. Therefore, the trend of long-term coexistence of 4/5G networks cannot be changed temporarily. Therefore, it is urgent to study the optimization of 4/5G dual-mode network collaboration and create a high-quality mobile network with good coverage, balanced capacity, and high user satisfaction, which has significant practical significance.

Based on the research of the current situation and collaborative optimization technology of 4/5G networks at home and abroad, this science combines the actual situation of a 4/5G network collaborative optimization project of a certain telecommunications operator. Through a large number of visits to the pain points of frequent user complaints about network problems, the ElasticNet network management control platform is used to extract and calculate abnormal network KPI indicators. The network problems at the two levels of coverage and capacity are used as the judgment basis. Tools such as MapInfor or Google Earth are used to import base station work parameters to create sector coverage layers, in order to predict basic information such as the coverage radius of each cell, the azimuth angle and downward tilt angle of the antenna in advance, divide the areas to be optimized, and establish optimization goals; Then prepare the vehicles, GPS, terminal devices, and Dingli Pioneer testing software required for data collection, and carry out CQT or DT data collection. Focusing on the two major network issues of "coverage" and "capacity", combined with KPI anomaly indicators, Pioneer is used to analyze the signaling of the logs collected on site. Based on the collaborative optimization threshold parameter setting model, the optimal 4/5G collaborative optimization scheme is analyzed and designed, and the problems in the network are gradually solved according to the priority order of optimization. Subsequently, we will discuss with the client to improve the loopholes in the optimization plan and ensure that it is more reasonable. Next, implement the optimization plan and complete the optimization tasks item by item. Finally, compare the results before and after optimization, continuously improve the optimization plan to achieve the expected optimization goals, complete the writing of the optimization report, and share the optimization results.

In response to the network problems of weak coverage areas at the 5G edge and high LTE load areas at the capacity level, a 4/5G network collaborative optimization scheme was implemented to increase the average SS-RSRP(Synchronization Signal Reference Signal Received Power) of 5G at the coverage level from -109.3 dbm to -103.5 dbm, an increase of 5.6%; At the same time, in terms of capacity, the average utilization rate of downlink PRB in 25 SA cells of 5G has increased by 19.05%. From this, it can be seen that the LTE network load is greatly reduced, which to some extent diverts the capacity pressure of the 4G network from the 5G SA network, and the capacity load balancing effect is obvious. Therefore, the feasibility of the proposed 4/5G network collaborative optimization scheme design has been verified through 4/5G network collaborative optimization, providing certain ideas and references for subsequent 4/5G network collaborative optimization.

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