# Quality of Experience in 6G Networks: Outlook and Challenges
## 1 Introduction  
According to 5G Americas, there are 135 live deployments worldwide for the 5G network, with the bulk of networks (~60%) deployed in Western Europe and the Asia-Pacific region at the time of writing the report [1]. Comparatively, the current numbers of worldwide deployments for LTE (long term evolution) and LTE-Advanced are 680 and 338, respectively. The current number of 5G deployments is expected to increase, as these deployments are in response to the first relevant 3 GPP release (Release 15) made in 2018 Q2 and the Phase 2 release (Release 16), just recently made in 2020 Q3 [2]. Release 17 currently has its timeline under review, with a decision on the freeze to be made in December 2020. The release aims to offer further features in 5G networks [3]. Different projections suggest that 5G networks are expected to account for 20% of mobile connectivity in 2025 [4]; considerable investments are thus naturally underway. However, while 5G deployment is still ongoing, and even with ambivalent consumer reception to deployments that have already been made, substantial discussions are already underway regarding technologies and services in 6G networks [5]. Operators such as NTT Docomo [6] and vendors such as Samsung [7] and Ericsson [8] have readily released white papers detailing possible visions. Meanwhile, initiatives such as the University of Oulu's \"6G Flagship\" have sought input from leading researchers and practitioners, who have offered insights on various considerations of 6G networks through detailed positions and vision papers [9]. A basic Google Scholar search for \"6G (cellular OR wireless)\" limited to \"since 2019\" yields over 17,000 hits today. There is also a plethora of journal and magazine special issues and dedicated workshops already receiving submissions. There is substantial consensus on the awaited enabling technologies and the distinguishing (or \"killer\") services as we look beyond 5G networks [10, 11]. Some reports suggest that the earliest 6G deployments may occur during 2028-2029, with projections on the downlink data rate reaching ambitious data rates at terabits per seconds (Tbps) [12]. However, the expected focal characteristic of 6G networks is autonomous intelligence. This expectation is not limited to the user's view but also to that of the network operator. Indeed, where 5G has been marked by a strong emphasis on thorough softwarization and resource virtualization [13], the general expectation is that 6G will capitalize on advancesin artificial intelligence and inference, with applications of these advances considered at all levels of network operation. The general interest in shifting towards autonomous intelligence has long been anticipated, especially to overcome decision complexity in different network elements. For example, the complexity of managing the radio resource has already overwhelmed traditional solution approaches since Release 12 [14, 15, 16]. This complexity is particularly apparent in appropriating the best resource management option to the individual user's needs or circumstances and in deciding on this appropriation through the set scheduling constraints. Addressing this rising concern in radio resource management (RRM), various AI-based architectures have been proposed (e.g., [17, 18]). Deliberations on these solutions have ultimately resulted in 5G's NWDAF (network data analytics function) as part of the core network [19]. NWDAF interacts with the virtualized network instances (slices) to provide the operator with an analytics-based view of the network state. The introduction of other AI-based network instances can also be traced, and these are expected to be further materialized as the development of 6G specifications proceeds. The complexity in network management came as a result of the increasing demand. It has been observed that the growth in the numbers of mobile subscribers has plateaued in recent years.