Updating analysis of key performance indicators of 4G LTE network with the prediction of missing values of critical network parameters based on experimental data from a dense urban environment

Abstract

In practice, field measurements often show missing data due to several dynamic factors. However, the complete data about a given environment is key to characterizing the radio features of the terrain for a high quality of service. In order to address this problem, field data were collected from a dense urban environment, and the missing parameters were predicted using the Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) algorithm. The field measurement was taken around Victoria Island and Ikoyi in Lagos, Nigeria. The test equipment comprises a Global Positioning System (GPS) and a Fourth Generation (4G) Long Term Evolution (LTE) modem equipped with a 2×2 MIMO antenna, employing 64 Quadrature Amplitude Modulation (QAM). The Modem was installed on a personal computer and assembled inside a test vehicle driven at a near-constant speed of 30 km/h to minimize possible Doppler effects. Specifically, the test equipment records 67 LTE parameters at 1 s intervals, including the time and coordinates of the mobile station. Thirty-two parameters were logged at 42,498 instances corresponding to 11 h, 48 min and 18 s of data logging on the mobile terminal. Sixteen important 4G LTE parameters were extracted and analyzed. The statistical errors were calculated when the missing values were exempted from the analyses and when the missing values were incorporated using the PCHIP algorithm. In particular, this update paper estimated the missing values of critical network parameters using the PCHIP algorithm, which was not covered in the original article. Also, the error statistics between the data (histograms) and the corresponding probability density function curves for the measured data with missing values and the data filled with the missing values using the PCHIP algorithm are derived. Additionally, the accuracy of the PCHIP algorithm was analysed using standard statistical error analysis. More network parameters have been tested in the update article than in the original article, presenting only basic statistics and fewer network parameters. Overall, results indicate that only the parameters which measure the throughput values follow the half-normal distribution while others follow the normal distribution.