###### Abstract  
The main goal of this paper is to create an adaptive model based on multilayer perceptron (MLP) for prediction of average downlink (DL) data throughput per user and average DL data throughput per cell within an LTE network technology and in a geo-space that includes a segment of the Motorway 9 th January with the access roads. The accuracy of model prediction is estimated based on relative error (RE). With multiple trainings and testing of 30 different variants of the MLP model, with different metaparameters the final model was chosen whose average accuracy for the Cell Downlink Average Throughput variable is 89.6% (RE = 0.104), while for the Average User Downlink Throughput variable the average accuracy is 88% (RE = 0.120). If the coefficient of determination is observed, the results showed that the accuracy of the best selected prediction model for the first variable is 1.4% higher than the accuracy of the prediction of the selected model for the second dependent variable. In addition, the results showed that the performance of the MLP model expressed over R\({}^{2}\) was significantly better compared to the reference multiple linear regression (MLR) model used. predictive models; MLP; prediction; throughput; LTE; cell; model training; model testing; coefficient of determination Article  
Adaptive Modeling of Prediction of Telecommunications Network Throughput Performances in the Domain of Motorway Coverage  
M. K.  
has increased the awareness of end users about the importance of quality of service (QoS) and quality of user experience (QoE). For this purpose, three key wireless network performance indicators (_Key Performance Indicators_--KPIs) are used: _throughput_, _latency_ and _packet loss_. In this paper, the focus is on the research of the network throughput performance, and important throughput instances are _Downlink_ (DL) in the direction of _DL Throughput_ (DLT), i.e., the average throughput in DL direction _Average DL Throughput_ (ADT) used in systems for monitoring, reporting and comparing the quality of network traffic. The ADT value can be determined physically--continuously or discretely (by time), logically (by service) or geographically (by spatial unit). Most of the generated traffic in the mobile network is the DL traffic, directed from the base station to the user equipment. Thus, in this paper, the variables considered as output (dependent) ones are average DL throughput per individual _cell_ of the mobile network and average DL throughput per individual _user_ in the network along the selected road in the geo-area of the research. The standard used is _Long Term Evolution_ (LTE) which belongs to the fourth generation (4G) of the mobile cellular network technologies. The two observed dependent variables are important indicators of the current state of traffic in the mobile network, whose understanding is important for design and modeling, resource planning and control of operational readiness, functional suitability and reliability of the network, and their values are significantly reflected on the level of the network quality of services (QoS) and on the level of quality of user experience (QoE). Accordingly, the subject of research in this paper is the predictive modeling of variations of the value of the average DL throughput in a mobile network at the cell level and at the user level that will allow us to further define/monitor QoS and QoE. A segment of the _Motorway 9 January_ (M9)), a key road in Republika Srpska, located in the northern part of Bosnia and Herzegovina, was selected for the case study in the geo-space of research. The length of that road segment is 72 km, between the two locations of toll collection (Pay toll)--Jakupovci near Banja Luka (BL) and Johovac near Doboj (Db). In the topological structure with this segment of M9), the research also includes a part of the road (about 6 km) on the route Jakupovci--BL and also a part of the main road M17, Johovac--Db (about 10 km).