Thanks to the availability of mobile devices and the spread of broadband access around the world, the number of network users continues to grow. This has raised user awareness when it comes to the quality of content they consume. Many service providers and operators focus on monitoring QoN (Quality of Network) and QoS (Quality of Service) parameters, particularly those influenced by bandwidth and latency. However, for most end-users, quality is understood as the subjective QoE (Quality of Experience), a mixture of several individual factors. This paper presents a QoN evaluation, carried out under real-time operating conditions at a university campus, considering the overall performance of the cellular network. The study involved 50 mobile devices, i.e., smartphones, used by students during their typical activity throughout a week. The results were gathered on the eve of 5G, using a custom-built Android application. This application enabled the acquisition of valuable data about the wireless link, including download and upload speed, latency (pink), the ID of the serving base station, and type of cellular connection. This approach can be used to detect the strengths and weaknesses of back-end networks.

The COVID-19 pandemic has significantly limited user mobility, not least among students. Remote learning had a particular impact on resource allocation in relation to using terrestrial cellular networks, especially 4G systems in urban agglomerations. This paper presents the results of a quality evaluation of an outdoor environment, carried out between 2019 and 2021 on the campus of a technical university. Annual studies are conducted using our own custom-built mobile application, installed on 50 mobile devices (i.e., smartphones) running Android OS. This study aims to determine the impact of reduced user mobility on access parameters in mobile networks, that is, both download and upload throughput as well as delay (ping), with a particular focus on serving base transceiver stations (BTSs). This research scenario involves long-term evolution (LTE) compatible user equipment (UE) that operates under four Polish mobile network operators (MNO), which includes roaming connections and the newly launched 5G standard.

Recently, many researchers have been intensively conducting quality of service (QoS), quality of experience (QoE), and user experience (UX) studies in the field of video analysis. This paper is intended to make a new, complementary contribution to this field. Currently, streaming platforms are key products in relation to delivering video content online. Most often, they include the MP4 video format, which is most widely utilized among audio-visual codecs. This study involves a group of 38 individuals, aged between 21–35 years old, in a laboratory consisting of 20 iMacs with 4K retina display. The presented signal sequences included content sourced from the Netflix Chimera repository, with 8- and 10-bit depth, available in different resolutions of 270p, 432p, 720p, and 1080p. Tests included a subjective quality evaluation in a 5-step mean opinion score (MOS) scale, focused on the UX aspect. According to the obtained results, content with the lowest and highest resolutions is optimal in 8-bit depth, while movies with intermediate resolutions are better in 10-bit depth. For 8-bit content, the main problem is pixelation, whereas, in the case of 10-bit samples, the main issue is color noise, particularly in the case of the lowest resolution. Many viewers indicated that 10-bit encoding offered lower quality. Moreover, 8-bit movies caused a lower quality of the gradient, presumably due to the smaller range of the available color. However, 8-bit movies in the same situation generate visible stripes on static images in the background, causing a lower quality of the gradient, which is probably due to the smaller range of available colors. The results of the performed experiments may be of particular interest to content creators and distributors, particularly network and cable operators, as well as wireless and wired providers

With the advancements in mobile navigation, and thanks to the availability of portable devices, it is possible to calculate the trace and continuously monitor a user’s position. Due to widespread access to smartphones, any person can easily check their location, regardless of where they are at a given moment. This becomes an important factor in everyday life, especially while driving a car in an urban environment or agglomeration. In addition, mobile network operators and service providers themselves use location-based information to monitor and improve the quality of their services. This paper presents the results of a measurement campaign, which was carried out using Android-powered smartphones. The analysis includes four devices, originating from different manufacturers, with varying technical specifications, particularly supporting global navigation satellite systems (GNSSs). The data were gathered while driving a car in various surroundings, including natural as well as manmade objects. The outcomes of the performed experiments may be of particular interest to both scientists and practitioners who rely on navigation systems and services on a daily basis.