# Optimizing the Quality of Service of Mobile Broadband Networks for a Dense Urban Environment
## 2 Theoretical Background
### Related Work  
In 2022, [PERSON] et al. analyzed the KPIs of 4G LTE networks, essentially applying the piecewise cubic Hermite interpolating polynomial (PCHIP) algorithm to mitigate the effect of missing data obtained during a driving test (DT) in a dense urban environment [17]. Their observance of a half-normal distribution for the parameters more connected with the throughput is a good indicator that MNOs have maintained a skewness towards obtaining better data transfer rates. Furthermore, while trying to curb the inevitable data loss due to poor distance and other environmental factors such as building density, they compared the data with missing values to a filled data set and found no significant difference between them. For academic and industrial purposes, [PERSON] et al. conducted indoor and outdoor evaluations of 5 MNOs in Malaysia [1]. The study presented the operational levels of the signal quality and uplink and downlink throughput. To clearly define critical differences in the observed MNOs, the study stretched to less-considered parameters such as the ping and handover of all the network providers. Since the study focused on describing the overall QoE and other related network issues, the equipment used during measurements had 3G and 4G network compatibility. Going by these developments, [PERSON] et al. [18] explored the low-density parity-check (LDPC) and polar codes conducive to 5G operation. They also compared these codes to the operating codes for 4G LTE. For a work targeted towards confirming the viability of the promise of a seemingly better communication technology that enables high-reliability connections, they spelled out the implication of using new 5G codes and the potential performance of a 5G architecture. On a practical note, however, [PERSON] et al. [21] presented real-world deployment parameters while successfully integrating coplanar waveguide (CPW)-fed antennas and other simple devices to produce a special 4G LTE band known as category 7. The experiment was targeted toward smartphones, and a typical smartphone was used. Despite the improvements presented by 5G technology compared to the 4G LTE and older generations, there is still a need for periodic and empirical performance evaluation of cellular network technologies. Although signal coverage, among other parameters, is essential to determining the QoS of a wireless network, signal quality is also relevant. According to [PERSON] et al., and other researchers, 4G has better signal quality, while 4G LTE network has a range of signal coverage [18; 22]. While the world speeds off into the adoption of 5G technology, the potential of the 4G network has not been fully harnessed and designed to have repeating patterns in its frequency to curb the problems of channel irregularities, frequency error, and time lag; a 4G network may be just enough to meet the average user requirements. One of the problems experienced most of the time concerning the QoE a user receives is due to service providers not meeting the standard specifications contained in the 3 GPP. Coupled with the fact that different environmental conditions are left to the providers to address based on their hardware assets and the skills of their operators, the lack of implementation of the standard 3 GPP signals provides a platform for estimating the time of arrival (TOA) in areas with MBB signal deficiencies, as discussed in [23]. In a work aimed at solving the problem of poor mobile network performance problem in Brazil, a limited region with poor networking infrastructure and coverage was selected. The number of base transceiver stations (BTS) and the power they transmitted for optimal coverage of the region were then analyzed, as presented in [24]. Based on social cloud computing, there have been suggestions of models that use image measurements to optimize the QoS and QoE [25; 26; 27; 28] of wireless networks. The limitation, however, is that these suggestions do not include practically implementable mappings for achieving the models [11].